DSTYK inhibition increases the sensitivity of lung cancer cells to T cell–mediated cytotoxicity

Prioritization of tyrosine kinases identifies DSTYK as a prevalent alteration in NSCLC patients

Aiming to search for novel kinases involved in lung cancer, exome analysis was performed in murine lung LUSC cell lines generated in our group (Valencia et al., 2021), leading to identify the tyrosine protein kinase Dstyk (dual-serine/threonine and tyrosine protein kinase) as a potentially interesting mutated gene for study in lung cancer (Fig. 1 A). In order to explore the clinical relevance of DSTYK alteration in lung cancer, we analyzed The Cancer Genome Atlas (TCGA) data and we found around 6.4% of lung cancer patients were reported to have alterations in DSTYK (Fig. 1 B). According to the TCGA dataset, CN gain affected a greater number of patients (4%) than mutations (2.4%) in the DSTYK gene. These percentages of alteration were comparable to those for most of the druggable targets in lung cancer, except for EGFR and K-RAS (Jordan et al., 2017; Campbell et al., 2016). Mutations were distributed homogenously throughout the gene sequence and showed no characteristic pattern or hot spot regions that would merit particular attention. Therefore, we decided to focus on the potential functional relevance of DSTYK genetic CN gain. In order to study the percentage of NSCLC patients with DSTYK CN gain, we compared the DSTYK CN in tumor samples and samples from healthy lungs from the TCGA cohort. Tumors showed a significant increase in DSTYK CN compared to normal lung (Fig. 1 C). More importantly, in the subgroup of patients where matched tumor and normal sample was available, increase in CN was found for 82% of cases (Fig. 1 D). The average DSTYK gene CN in tumors was 2.31 ± 0.011. Moreover, patients with DSTYK CN gain showed a poor survival rate (Fig. 1 E). Therefore, these data suggested that DSTYK was altered in NSCLC patients and that genomic gain/amplification might be relevant to the tumorigenic process in a percentage of NSCLC patients.

As expected, the DSTYK CN was significantly correlated with DSTYK mRNA levels and patients with DSTYK CN gain (CN variation [CNV] ≥ 3) showed significantly higher mRNA expression (Fig. 1 F). Furthermore, in the Kaplan–Meier plotter dataset, patients with DSTYK expression in the first quartile (Q1) showed significantly worse progression-free survival (PFS) and OS rates (Fig. 1, G and H).

After obtaining a general picture of DSTYK alteration in NSCLC, we then studied CNV separately in LUAD and LUSC. We observed DSTYK CN gain (three or more copies) in 4.7% of LUAD and 3.4% of LUSC patients, respectively (Fig. 1 I).

To confirm publicly available data, we assessed DSTYK CN by qPCR in a series of 45 frozen samples from NSCLC patients who underwent surgical resection at the Clínica Universidad de Navarra (CIMA-CUN; Table S1). According to our analyses, 13.3% of patients showed a gain of DSTYK CN (Fig. 1 J). Fluorescence in situ hybridization (FISH) was performed to corroborate these results in formalin-fixed, paraffin-embedded samples from the same cohort. We observed that 25% of cancer cells showed three or more copies in those patients where DSTYK was found to be amplified by qPCR (Amp DSTYK) and 17% in patients with DSTYK CN < 3 by qPCR (NoAmp DSTYK). More interestingly, among cells that displayed DSTYK CNV by qPCR, Amp DSTYK patients presented 4.3 copies on average while 3 copies on average were counted in NoAmp DSTYK patients. Moreover, the maximum mean number of DSTYK copies found in altered cells in Amp and NoAmp DSTYK patients was 5.3 and 3, respectively (Fig. 1 K). The observed alterations in DSTYK CN were not due to aneuploidy as two centromeric copies from chromosome 1 were counted in all cases.

Finally, to confirm the correlation between CN and transcript levels of DSTYK, we performed a Western blot analysis of frozen tumor samples from CIMA-CUN cohort patients with DSTYK CN gain and diploid number. We observed higher levels of DSTYK protein in patients with CN gain comparing to those with diploid DSTYK, which showed low DSTYK protein levels (Fig. 1 L).

In order to explore the clinical relevance of DSTYK alteration in other human cancers, we analyzed TCGA data, and we found widespread incidence of CN gain and/or mutation in DSTYK across cancer types (Fig. S1 A). Alterations were highly prevalent in many cancer types and were found in >20% of patients with hepatocarcinoma, breast cancer, or cholangiocarcinoma and around 15% of patients with melanoma, ovarian, or uterine carcinoma, which suggests that DSTYK alteration was important in a very relevant number of human cancer types.

Taken together, these findings suggested that amplification of DSTYK was commonly altered in NSCLC and showed prognostic relevance in lung cancer patients.

DSTYK is located in autophagosomes where it performs its molecular functions

The function and subcellular location of DSTYK within the cell remain largely unknown. Through cellular fractionation experiments in murine and human lung cancer cell lines, we observed DSTYK was enriched in the microsomal fraction (Fig. 2 A). To delve into the nature of vesicles that were associated with DSTYK, we studied markers from the main vesicles by immunofluorescence (IF) in a Flag-DSTYK cell line. We observed that DSTYK, together with the autophagy marker LC3, co-localized in large, rounded cytoplasmic structures mainly located at the periphery of cells. The shape and LC3 protein location in these structures pointed to the fact that DSTYK was mainly located in autophagosomes (Fig. 2 B and Fig. S2 A). We assessed a proximity ligation assay (PLA) to corroborate that DSTYK and LC3 were in close proximity, verifying both markers were part of a single structure, located at least in contiguous spots (40 nm of maximum distance) and configured autophagosomes in a cooperative way (Fig. 2 C). Flag (DSTYK) signal did not co-localize in any other of the evaluated vesicle types, for which IF markers were used (Fig. S2 B).

Autophagy has been associated with carcinogenesis in several tumor types including lung cancer (Nam, 2021). To confirm whether DSTYK role was related to autophagy in lung cancer and to ascertain the potential molecular carcinogenesis processes in which DSTYK was involved, we performed an RNA sequencing (RNAseq) analysis of two different lung cancer cell lines with either overexpressed or inhibited DSTYK. Inhibition was achieved through shRNA technology (Fig. 2 D). After data filtering, we observed a significant enrichment of genes related to lysosomes, autophagy, mitochondria, oxidative stress, and cytoskeleton. These genes were differentially expressed in an altered DSTYK context (Fig. S2 C and Table S2). We confirmed these shRNA-based results in two independent DSTYK-CRISPRed partially KO cell lines, both murine and human (Lewis lung carcinoma [LLC] and H2009, respectively; Fig. S2 D). The altered RNA expression data from both technologies (shRNA and CRISPR) supported the previous data obtained through protein analysis of fractionated cell compartments and the morphological IF results. The integrated interpretation of these experiments strongly suggested that DSTYK was involved in autophagy processes presumably related to mitochondria (mitophagy).

In order to further dissect the potential molecular role of DSTYK in autophagy in a lung cancer context, we evaluated the DSTYK protein interactions in lung cancer cell lines by immunoprecipitation followed by mass spectrometry. These experiments yielded several interesting proteins (Table S3 and Fig. S2 E). Among these proteins, consistent with our transcriptomic and proteomic results suggesting a role for DSTYK in autophagy, we validated a protein–protein interaction of DSTYK with P62 (SQSTM1; Fig. 2 E). P62 is upregulated in many cancer types. It is a key participant in the formation of the autophagosome, first identified as an autophagy adaptor, residing in the late endosome lysosome (Moscat and Diaz-Meco, 2009).

To further elucidate the specific molecular role of DSTYK in autophagy in lung cancer, we analyzed the expression or activation of key members of the autophagy cell protein pathway in our CRISPRed cellular models. We found an increase in p-S6K, LC3, and p-P62 in DSTYK KO cells compared to parental cells, which suggested that DSTYK inhibited mTORC1 and, consequently, fueled autophagy. To verify that the phenotypes observed were mediated by mTOR, we treated KO cells with rapamycin (mTOR inhibitor), recovering the autophagy values of parental cell lines (Fig. S2 G). Moreover, other mTOR-related functions such as glucose uptake were impacted by DSTYK inhibition (Fig. S2 G). These data were consistent with previous work reporting a role for DSTYK in regulating mTORC1 in zebrafish models (Sun et al., 2020). Nevertheless, the accumulation of p-P62 (and stable total P62) protein that we found in DSTYK inhibited lung cancer cell lines suggested that the autophagosome content was not being processed; this indicated that the autophagic process was not fully functional in these cell lines (Fig. 2 F). To verify that DSTYK inhibition interrupted autophagy, we treated parental cells with chloroquine, which showed a similar pattern of autophagic markers to DSTYK KO cells (Fig. S2 H). In summary, these data suggested that DSTYK induces autophagy, and its deficiency caused autophagy interruption, which led to a progressive accumulation of autophagosomes.

mTORC1 is known to phosphorylate TFEB/3, avoiding its nuclear translocation and preventing the expression of its target genes, which trigger lysosome biogenesis (Roczniak-Ferguson et al., 2012). Having found Lamp1 to be downregulated in DSTYK KO cells, we hypothesized that DSTYK could also regulate lysosome biogenesis in lung cancer. For this purpose, we studied the presence of TFE3 and LAMP1 proteins in the nucleus and in the cytoplasm, and we observed that DSTYK KO cells showed reduced levels of nuclear TFE3 and subsequently reduced levels of LAMP1 (Fig. 2 G). Therefore, the absence of DSTYK negatively affected lysosomal biogenesis.

To further assess the effects of DSTYK on lysosome function, we measured their pH in parental and KO human and murine cells. Surprisingly, lung cancer cells lacking DSTYK expression showed less acidic pH (5.6 ± 0.08) in lysosomes than parental cells (4.6 ± 0.2), suggesting an impaired lysosomal functionality (Fig. 2 H). This fact was in accordance with the lower expression of V-Atpases shown in DSTYK knockdown cells in the RNAseq analysis (Fig. S2, C and D), which might partially explain a dysregulation in proton uptake in KO cells lysosomes among other possible mechanisms.

Our data, thus, strongly supported an involvement of DSTYK in molecular pathways related to autophagy through its interaction with the key autophagy regulating protein P62.

DSTYK regulates the NRF2 pathway

Since P62 is also a key regulatory protein of the KEAP1-NRF2 pathway and we found oxidative stress genes expression to be increased upon DSTYK inhibition (Table S2 and Fig. S2 B), we assessed the implication of DSTYK KO in this scenario. Through Western blot experiments, we showed that the increase in P62 consequently to DSTYK knockdown led to a greater interaction P62-KEAP1, which allowed NRF2 to translocate to the nucleus and expressed its target genes such as HO1 or NQO1, involved in the oxidative stress response (Fig. 3 A).

Taken together, these results suggested that DSTYK could modulate oxidative stress response.

Oxidative stress can be triggered by ROS as a consequence of mitochondrial respiration. Following our RNAseq and immunoprecipitation data pointing to a functional role of DSTYK in mitochondrial biology, we studied mitochondrial functionality in our models. As compared to parental cells, ROS levels in KO cells under normal conditions were dramatically increased (Fig. 3 B). ROS production may be due to dysfunctional mitochondrial respiration. To further investigate the potential functional alteration in mitochondria, we performed a mitostress test (Seahorse). Under basal conditions, the two types of cells did not exhibit respiratory differences (Fig. S3 A) but under stress conditions, DSTYK KO cells did not respond to the FCCP treatment, which is a potent mitochondrial oxidative phosphorylation uncoupler that disrupts ATP synthesis by transporting protons across mitochondrial inner membranes and depolarizes mitochondrial membrane potential, displaying a reduced maximal respiratory and spare respiratory capacities (Fig. 3, C and D).

These data suggested that DSTYK sustains mitochondrial fitness, and its depletion triggered mitochondrial dysfunction and consequently raises oxidative stress conditions.

DSTYK maintains mitochondrial integrity

An increase in ROS production may be the consequence of a loss of mitochondrial membrane (Zorova et al., 2018). To further investigate the integrity or potential functional alteration in mitochondria, we performed an in vivo IF, monitoring mitochondria within parental and KO cells with Mitotracker Green and tetramethylrhodamine methyl ester perchlorate (TMRM) fluorescent dye, to assess its membrane potential (Momcilovic et al., 2019; Fig. 4 A). In parallel, in an independent experiment, we evaluated and quantified labeled cells by flow cytometry. In normal conditions, cells showed no differences neither in mitochondrial mass nor in membrane potential. However, under stress conditions, DSTYK KO cells showed a dramatic TMRM reduction (loss of 98.5%) and a significant increase in mitochondrial mass (gain of 327%; Fig. 4, A and B; and Fig. S4 A). These results were in agreement with our previous data, suggesting that in DSTYK KO cells mitochondria were damaged, and cells were incapable of eliminating them through selective autophagy (mitophagy). This is likely the consequence of a deficient autophagy, and subsequently, damaged mitochondria were accumulated. Notably, ring-shaped mitochondria were observed in DSTYK KO cells under stress conditions, which is a sign of their damage (Ahmad et al., 2013; Fig. S4 B). To better understand mitophagy alterations in the absence of DSTYK, we tracked in vivo mitochondria and lysosomes by multiphoton confocal microscopy. In parental cells, we found that most foci of active mitophagy, surrounded by lysosome accumulation, exhibited a complete lack of mitochondrial labeling, whereas, in DSTYK KO cells, mitochondria were not able to be eliminated in those spots and lose TMRM labeling along time (Video 1 and Fig. 4, C and D). More importantly, under stress conditions, lung cancer DSTYK KO cells succumbed to ROS levels and accumulation of undigested mitochondria and died. In contrast, parental cells conserved the cytoprotective autophagy and normal mitochondrial respiration as mechanisms of cell survival and tumor progression (Fig. S4 C).

In conclusion, these data showed the involvement of DSTYK in the maintenance of an operative mitophagy and its depletion affected mitochondrial morphology, physiology and interrupted mitophagy.

DSTYK inhibition impairs tumorigenesis in vivo by sensitizing lung cancer cells to TNF-α–mediated CD8⁺ killing

In the organism, cancer cells face different stresses such as hypoxia, nutrient deprivation, or immunosurveillance. To assess the functional effects of DSTYK decreased levels in vivo, we performed experiments in syngeneic mouse preclinical models. We used cell lines from the main histological subtypes of NSCLC: LUAD and LUSC (LLC and UN-SCC680, respectively) and inhibited DSTYK using an inducible vector (Tet-pLKO) that activated an shRNA against DSTYK upon doxycycline administration (Fig. S5 A). The generated cell lines with inducible DSTYK-knockdown showed no cell proliferation differences in vitro (Fig. S5 B). sh#DSTYK was activated after tumor establishment in vivo (75–100 mm³ in size) by doxycycline administration. Both models showed a dramatic decrease (P < 0.001) in tumor size under DSTYK inhibition, which was directly proportional to the inhibition degree achieved by the sh#DSTYK, achieving tumor regression in both syngeneic models 2–3 wk after tumor cell injections (Fig. 5 A).

To understand the mechanism by which DSTYK depletion affected tumor size without modifying cell proliferation, we evaluated DSTYK expression levels in tumors at the end point of in vivo experiments by Western blot (Fig. S5 C). Surprisingly, we observed similar DSTYK expression levels in parental and DSTYK inhibited tumors, indicating that a very potent selective pressure was being produced against DSTYK KO cells in vivo, and only the clones that maintained DSTYK expression were able to survive and grow. Therefore, DSTYK was a dependency of lung cancer cells required to cope with stress in vivo.

Because DSTYK inhibition sensitized cells to stress and immune cells may threaten tumor stability, we hypothesized that the immune system could be mediating these potent rejections shown in our syngeneic models upon DSTYK ablation. First, to distinguish the direct growth effects of DSTYK depletion on cells from the effects derived from its interaction with the immune system, we performed a subcutaneous injection of control and sh#DSTYK murine cells in immunocompromised mice (Fig. S5 D). DSTYK inhibition did not affect cell proliferation in vivo suggesting that the effect observed in the syngeneic models might be non-autonomous and related to the immune system. To identify the effector cells responsible for these rejections, key immune populations were selectively depleted in vivo in parallel experiments. Elimination of CD8⁺ T cells completely abrogated the antitumoral effects of DSTYK knockdown in LLC tumors. However, neither CD4⁺ T nor natural killer depletion had any impact on LLC tumor rejection (Fig. 5, B and C). These effects were verified in an independent LUSC model: UN-SCC679 (Fig. 5 D). These results suggested that DSTYK depletion sensitized lung tumor cells to the action of cytotoxic CD8 cells.

To validate the role of DSTYK in limiting tumor cell killing by T cells, we assessed the behavior of CRISPRed KO cells in co-culture in vitro. DSTYK depletion sensitized LLC cells to T cell killing in vitro, dependent on T cell/tumor cell ratio excluding off target effects (Fig. 5 E). We next explored the mechanism by which CD8⁺ T cells were killing. A recent work showed how autophagy inhibited TNF-α–induced apoptosis (Young et al., 2020). In our cells, CD8⁺ T cell killing was reversed by capturing and blocking TNF-α with etanercept (Fig. 5 F). However, no effect was observed upon INF-γ treatment (Fig. S5 E). Consistently, tumoral killing by T cells was mimicked upon TNF-α treatment in KO LLC cells (Fig. 5 G). Similar results were observed in human cell lines (Fig. 5 G). These results were consistent with above-mentioned publication.

Interestingly, when we inhibited mTOR with rapamycin in KO cells, we rescued a parental phenotype, resistant to TNF-α–mediated killing (Fig. S5 F). Besides, parental cells treated with chloroquine, which prevent autophagy, became sensitive to TNF-α–mediated killing similarly to DSTYK KO cells (Fig. S5 G).

To verify whether these effects were maintained in vivo, parental and DSTK KO LLC tumor–bearing mice were treated with etanercept every 2 d after cell inoculation to block TNF-α. DSTYK-KO tumors treated with etanercept rescued the parental cell phenotype, results were consistent with those previously observed in vitro (Fig. 5 H).

In order to clarify the underlying cell death mechanism related to DSTYK depletion and TNF-α–induced apoptosis, we exposed H2009 parental and KO cells to stress conditions and we observed an increase of both activated caspase and p-MLKL in KO cells (Fig. S5 H). Thus, cell death related to DSTYK inhibition seemed to involve both caspase-dependent and independent mechanisms.

To dynamically understand the immune mechanisms that mediated tumor rejection in the absence of DSTYK, we performed intravital microscopy studies. Inducible sh#DSTYK LLC lung cancer lines were transfected with fluorescent proteins and injected subcutaneously into fluorescent T lymphocytes reporter mice. We dynamically observed that fluorescent T cells successfully attacked and eliminated knockdown-DSTYK tumors in 72 h, whereas parental tumors were insensible to T cell killing (Video 2 and Fig. 5 I). Our results showed a significant increase (P < 0.001) in apoptotic tumor cells per field in DSTYK-inhibited tumors but no differences in the number of intratumoral T cells (Fig. 5 J), suggesting that tumor elimination was a consequence of tumoral T cell killing sensitizing rather than tumor immune infiltrate changes.

To determine whether there was a therapeutic index for targeting DSTYK, we overexpressed the protein in immortalized human lung epithelial cells (3KT), and we demonstrated that amplification resulted in a gain of function both, raising autophagy markers and acquiring resistance to TNF-α treatment (Fig. S5, I and J). Interestingly, when we overexpressed Dstyk mutation found in UN-SCC680 in an independent murine cell line LLC, tumors of KO overexpressing mutated-DSTYK bearing mice rescued parental tumor growth (Fig. S5 K).

DSTYK inhibition sensitizes lung cancer cells to immunotherapy

Despite great advances in oncological therapies, still a high percentage of patients remain refractory to current treatments (Grant et al., 2021). More personalized treatments are required in NSCLC, not only to expand the targeted therapy but also to design immunotherapy regimens according to the individual NSCLC patient immune and genetic landscape (Wang et al., 2021b). We postulated that DSTYK downregulated could sensitize lung cancer tumors to immunotherapy. To test this, we treated our syngeneic mouse models harboring wildtype or DSTYK-deficient tumors with checkpoint inhibitors. For that, we selected our LLC CRISPRed model. Established LLC tumors, normally refractory to checkpoint inhibitor treatments, partially responded to anti–PD-1 administration under DSTYK inhibition conditions, showing a synergistic effect (Fig. 6 A).

More importantly, to confirm the translational value of our findings, we carried out a study on a cohort of 76 patients treated with ICI, for which both outcome and genomic traits were known (Frigola et al., 2022). According to our analysis, lung cancer patients who underwent immunotherapy and presented DSTYK amplification showed poorer PFS rates (P = 0.06). On average, the median PFS time for patients with DSTYK amplification was 11 mo, whereas 4.2 mo was the median PFS for patients with only two DSTYK genomic copies (Fig. 6 B). These results suggested DSTYK amplification as a predictive biomarker for immunotherapy resistance. More interesting, a combination of DSTYK inhibition and immunotherapy may be a potential strategy for lung cancer treatment where DSTYK blockage could sensitize tumor cells to ICIs.

Public data analysis

TCGA related data were downloaded from the TCGA bioportal using the TCGA biolinks R package (Colaprico et al., 2016). CNV and transcriptome profile data were downloaded for 24 cancer types. CN segment data type was used to measure the CNV in the segment where the DSTYK gene was identified. Log transformation was applied to define logCNV values. For transcriptome data, Gene Expression Quantification data were downloaded, quantified by HTSeq, and transformed in FPKM.

To assess the prognostic value of DSTYK expression, the online tool kmplot.com (http://kmplot.com/analysis/; Györffy et al., 2010) was used. The corresponding Affymetrix ID for DSTYK was 211514_at.

Cell lines and reagents

The human cell lines H2009 and H226 were purchased from ATCC. The human cancer cell lines were authenticated by the Genomics Unit at CIMA and grown according to ATCC specifications. The mouse LLC cell line was from the ATCC. UN-SCC679 and UN-SCC680 lung squamous carcinoma cell lines were previously established by our group from an N-nitroso-tris-chloroethylurea (NTCU) chemically induced mouse model (Valencia et al., 2021). 393P LUAD cells, derived from KrasLA1/+; p53R172 HΔG mice, were a gift from J.M. Kurie (The University of Texas MD Anderson Cancer Center, Houston, TX). All cells were cultured in RPMI 1640 medium (Invitrogen), 10% FetalClone (Thermo Fisher Scientific), 100 U ml⁻¹ penicillin, and 100 U ml⁻¹ streptomycin (Invitrogen). HBEC-3KT cells (Kerafast Inc.) were grown in keratinocyte medium (GIBCO). Only mycoplasma negative cells tested using the MycoAlert Mycoplasma Detection Kit (LONZA) were used.

Inducible knockdown constructs are as follows: Lentiviral transduction of shRNAs against DSTK (TRCN0000275831 [#1] and TRCN0000195393 [#2] for human; TRCN0000295440 [#3] and TRCN0000088496 [#4] for mouse; Sigma-Aldrich) was performed as previously described (Vallejo et al., 2017). Transduction of the empty vector (TetPLKO.1-puro; Sigma-Aldrich) was used as a control. CRISPR Cas9 strategy for DSTYK KO cell clones generation: single-guide RNAs complementary to the DSTYK sequence were designed using a GPP Web Portal tool from the Broad Institute (https://portals.broadinstitute.org/gpp/public/) and cloned into lentiCRISPRv2 plasmid from Addgene (Vallejo et al., 2017). Puromycin-resistant single cells were sorted in a p96 plate using MoFlo Astrios EQ (Beckman Coulter), characterized by quantitative RT-PCR (qRT-PCR) and Western blot analysis and expanded for experiments.

The single-guide RNA sequences used in this study are listed in Table S5.

Flag-DSTYK constructs are as follows: Flag sequence (5′-GAT​TAC​AAG​GAT​GAC​GAC​GAT​AAG-3′) was added to 5′-end DSTYK cDNA sequence and cloned in pBABE puro plasmid. Mouse LLC and UN-SCC679 cell lines were then infected to overexpress the tagged protein.

DSTYK overexpressing constructs are as follows: Wildtype mouse and human DSTYK cDNA sequence or mouse containing punctual mutation c.1976G>A were cloned in pLenti6/V5-DEST plasmid. Cell lines were then infected to overexpress the wildtype or mutated protein.

To induce stress, cells were cultured in RPMI 1640 no glucose (#11879-020; Gibco) or standard RPMI without the FetalClone supplement up to 24 h.

To impact the autophagy pathway, cells were treated with 25 µM of chloroquine (#C6628; Sigma-Aldrich) or 300 nM of rapamycin (#R8781; Sigma-Aldrich) for 24 h.

Glucose was measured in supernatant in Cobas c-311 analyzer using a glucose (HK) assay kit (#04404483; Roche) following the manufacturer’s instructions.

Whole-exome, shallow whole-genome, and RNAseq analysis

Shallow whole-genome sequencing data (cohort VH) were obtained from Frigola et al. (2022). For RNAseq, samples were prepared with the Illumina TruSeq Stranded mRNA kit following the manufacturer’s indications and sequenced as reverse paired-end (75 bp) runs on the Nextseq sequencer. For the RNAseq analysis, raw FASTQ files were trimmed with Trimmomatic/0.36. Pseudoalignment was carried out to the mm10 reference genome and gene level counts were determined with Kallisto (Bray et al., 2016). Quantification was carried out with 100 boostraps. Differential gene expression analysis was conducted with R using Sleuth R package (Pimentel et al., 2017). Significant genes were selected based on the false discovery rate–corrected P value <0.05. The following comparisons were carried out in the study: (A) LLC parental vs. (B) LLC sh#Dstyk; (A) UN-SCC679 parental vs. (B) UN-SCC679 O/E Dstyk wt; (A) UN-SCC679 parental vs. (B) UN-SCC679 sh#Dstyk.

Once differentially expressed genes were selected in each A vs. B contrast, all experiments were merged to verify the intersection of the genes based on name and the direction.

Immunoprecipitation

Flag-DSTYK and control cells were seeded in 150 mm² plates and incubated at 37°C until 80% confluency was reached. Cells were lysed (20 mM HEPES, 150 mM NaCl, 1% NP40, 10 mM MgCl₂ + phosphatase and protease inhibitors [#04906845001 and #11836170001; Roche]) on ice for 10 min and centrifuged at 13,000 g for 15 min at 4°C. Protein was quantified using the BCA assay kit (#23227; Pierce). 1 mg/ml of cell lysates was incubated with the indicated antibody (Table S5) overnight at 4°C. The day after, Dynabeads Protein G (#10003D; Thermo Fisher Scientific), were added and mixed for 2–4 h in rotation at 4°C. Immunoprecipitates were washed with lysis buffer five times and lysates were denatured in lysis buffer with LDS Sample buffer (NuPage #2201446) and β-mercaptoethanol (Sigma-Aldrich). Mass spectrometry was performed at the Harvard Medical School (https://taplin.med.harvard.edu/home). Eluted products were analyzed by Western blotting.

Western blotting and antibodies

After treatments were administered to plated tumor cells, these were washed with PBS and lysed in radioimmunoprecipitation assay buffer and with Nuclear and Cytoplasmic Extraction Reagents (NE-PER; cat #78835) plus phosphatase and protease inhibitors (#04906845001 and #11836170001; Roche). Lysates were centrifuged at 13,200 rpm at 4°C and quantified using a BCA protein assay kit (#23227; Pierce).

Samples were prepared using LDS Sample buffer (NuPage #2201446) and β-mercaptoethanol (Sigma-Aldrich). Protein samples were incubated for 15 min at 95°C before being loaded 10–50 μg on 10–15% acrylamide gels. Electrophoresis was performed in a running 10× Tris-Glycine SDS buffer, and nitrocellulose membranes were used for proteins transfer (#1620112; Bio-Rad). Membranes were incubated overnight with the indicated antibodies, washed with TBS-Tween, and incubated for 1 h with anti-rabbit (#GENA934; Sigma-Aldrich), anti-mouse (#NA931; GE Healthcare), or anti-goat (#P0449; Agilent) secondary antibodies.

Nuclear and cytoplasmic fraction extraction were performed using the NE-PER Nuclear and Cytoplasmic Extraction Reagents kit (#78835; Thermo Fisher Scientific) according to the manufacturer’s protocol: 100 μl of CERI and 5.5 μl of the CERII reagents for the cytoplasmic extraction and 50 μl of the NER reagent for the nuclear extractions, adding protease, and phosphatase inhibitors to CERI and NER to minimize reagent dilution.

For subcellular fractionation experiments, different cell fractions were obtained by serial centrifugation steps at increasing speeds.

Briefly, a pellet of cells was washed in cold PBS and then lysed in extraction buffer (Tris HCl pH8.5, 10 mM; NaCl, 150 mM; MgCl₂, 1.5 mM; IGEPAL, 0.5%; protease inhibitors). Cells were disrupted for 10 min on ice and then centrifuged at increasing speeds. Pellets and supernatants of serial centrifugations were recovered and then loaded onto an acrylamide gel with equivalent amounts of the obtained fractions. The following conditions were followed to obtain subcellular fractions: Total extract, cells pelleted and resuspended directly in Laemmli buffer 1×; nuclear extract (P3000), pellet of extraction buffer lysed cells centrifuged 2 min, 3,000 g, 4°C; cytosolic extract (S3000), supernatant resulting from the previous centrifugation step; Large organelle extract (P10000), pellet resulting from S3000 centrifugation 10 min, 10,000 g, 4°C; cytosolic extract without large organelles (S10000), supernatant resulting from previous centrifugation; microsomal extract (P100000), pellet resulting from S10000 centrifugation 2 h, 100,000 g, 4°C; coluble cytosolic extract (S100000), supernatant resulting from previous centrifugation.

Western blot band detection was performed using Image Studio software. Densitometry quantification was done using ImageJ (National Institutes of Health). All measurements can be found in Table S4.

The antibodies used are listed in Table S5.

qRT-PCR

Genomic DNA was extracted from frozen samples from the CIMA-CUN series and CN was measured by qPCR using the TaqMan Copy Number assay (#Hs01236436-cn for DSTYK and #4401631 for RNAse P; Applied Biosystems) according to the manufacturer’s protocol.

Total RNA from cells was isolated with the NucleoSpin RNA isolation kit (#740955; Macherey-Nagel). 1 µg RNA was used to synthesize complementary DNA using a High-Capacity cDNA Reverse Transcription kit with RNase inhibitor (#4374966; Applied Biosystems). Quantitative PCR was performed with the PowerUp SYBR Green PCR Master Mix (#100029284; Thermo Fisher Scientific). The primers designed for quantitative PCR are listed in Table S5.

FISH

DSTYK CNV was evaluated by FISH. Samples were dewaxed, hydrated, and heated in citrate buffer pH 6 for 30 min. Specimens were then treated with 4 mg/ml of pepsin in 0.01 N HCl for 5 min at 37°C and dehydrated. Next, a dual DSTYK1q32.1/CEN1p11.1 probe (Empire Genomics; #DSTYK-CHR01-20-ORGR) was added, denatured for 7 min at 75°C, and incubated 24 h at 37°C to allow hybridization. Samples were immersed in a post-hybridization saline-sodium citrate buffer (SCC; 0.3 M NaCl; 0.03 M sodium citrate; pH 7) for 2 min and then in SCC with 0.3% of NP-40 (Sigma-Aldrich) for 1 min at 70°C. Nuclei were counterstained with DAPI 1,500 ng/ml (#U0031; Abnovas). CNV variation was evaluated with a Nikon E800 microscope provided with a Nikon DS-Qi1-Mc camera and NIS-Elements software. Images were processed with ZEISS ZEN software.

IF

Cells were seeded in an 8-well culture slide (354108; Falcon) and cultured for 48 h. Then, cells were fixed with 4% formaldehyde methanol-free (28908; Thermo Fisher Scientific) for 10 min at 37°C and IF was performed in a BSA 1.5% saponin 0.05% buffer. All primary antibody incubations were carried out overnight at 4°C. Secondary antibodies were incubated for 1 h at room temperature. Nuclei were dyed with Hoechst (1:1,000). For negative control, cells were incubated directly with secondary antibody (1:100) 1 h at room temperature. Images were taken at 63× using a confocal microscope LSM 800 with Airyscan (Zeiss). IF antibodies are listed in Table S5.

For confocal microscopy experiments of mitochondrial and lysosome dynamics, parental, or DSTYK KO H2009 tumor cells (30,000 cells) were plated in 8-well LabTek microscopy plates (Nunc). 24 h later cells were stained using Mitotracker Deep Red (0.1 µM, Thermo Fisher Scientific), TMRM (125 ng/ml; Sigma-Aldrich) and Lysotracker Green DND-26 (0.1 µM; Thermo Fisher Scientific) for 20 min at 37°C in RPMI 10% FBS. The cells were then washed twice with warmed media and treated with RPMI glucose-free serum.

Time-lapse videos were recorded on an LSM880-inverted confocal microscope (Zeiss) equipped with an incubator to maintain 5% CO₂, humidity, and a temperature of 37°C throughout the experiment. Images were taken using a 40× water plan apochromat LD objective (NA, 1.2). An Argon 488 laser line and two He/Ne lasers (543 and 633 nm) were used to simultaneously excite the three dyes. 3D Z-stacks of 15–20 μm were obtained by acquiring images every 0.5–0.7 µm.

Intravital microscopy experiments

For intravital imaging, sh#DSTYK LLC cells were transfected with pMAX EGFP and isolated by FACS. 1 × 10⁶ LLC sh#DSTYK-EGFP cells were injected into the ears of hCD2RFP mice. 7 d after ear injection, sh#DSTYK was activated by adding doxycycline to drinking water for 24 h. Other tumors remained inactivated to maintain DSTYK expression. Then, intravital imaging in the mouse ears was performed. Anesthetized and temperature-controlled mice were placed on a custom-built stage and imaged with a LSM880-inverted microscope equipped with a 25× water immersion objective (NA, 0.8). Imaging sessions took from 2 to 4 h and time-lapse acquisitions in several regions of the tumor lasted 90 min with frames taken every 60 s. At least three mice were imaged per condition. Z-stacks were blindly selected according only to the presence of tumor cells. Videos were analyzed using IMARIS software, performing semi-automated surface-based segmentation to identify individual tumor cells, apoptotic tumor cells, and T cells. Time-lapse videos were generated with IMARIS software and edited with Final Cut Pro.

PLA

30,000 H2009 cells were plated in Lab-Tek Chambered coverglass (#155411; Thermo Fisher Scientific). After 24 h, cells were fixed and permeabilized 10 min with Triton X-100 0.5%. Primary antibodies were diluted to suitable concentration (1:500) and incubated overnight (Table S5).

Duolink In Situ PLA probes, MINUS mouse (#DUO92004) and PLUS rabbit (#DUO92002), and Duolink In situ Detection Reagents Red (#DUO92008) were obtained from Sigma-Aldrich. PLA assay was performed according to the manufacturer’s instructions.

Flow cytometry experiments

Mitochondrial mass and transmembrane potential were assessed by FACS staining. Parental or DSTYK KO H2009 tumor cells were cultured in complete media or glucose-free media overnight. Cells were then stained with Mitotracker Green FM 0.1 µM (#M7514; Thermo Fisher Scientific) and TMRM 125 ng/ml (#T668; Thermo Fisher Scientific) for 20 min at 37°C in RPMI 10% FBS. Cells were washed once with FACS buffer and analyzed in a Cytoflex S cytometer. Live cells were gated based on forward scatter (FSC) and side scatter (SSC) parameters and singlets were selected according to FSC-H, FSC-A parameters. Then, TMRM and Mitotracker Green fluorescence was assessed in the corresponding FITC and PE channels.

Mitochondrial respiration experiments

Mitochondrial respiration was measured using a Seahorse XFp Cell Mito Stress test kit (#103010-100; Agilent). Briefly, 15,000 cells of parental and KO LLC and 10,000 cells of the corresponding H2009 were seeded in triplicates in 8-well plates (#103022-100; Agilent). 24 h after seeding, cells were subjected to metabolic stress conditions through glucose or serum deprivation from 16 to 24 h. Plates were measured in a Seahorse XFp Analyzer (Agilent).

ROS measurement

120,000 cells were seeded in a 6-well plate, and after 24 h, a 50 µM DCFDA probe (#D6883; Sigma-Aldrich) was added for 30 min. Then, cells were trypsinized, pelleted, and resuspended in PBS. Fluorescence was measured in a Microplate Infinite Pro 200 reader (Tecan) in a black 96-well plate (#Rev. C/0815; PerkinElmer) at 485–530 nm (excitation-emission). Data were normalized by cell number.

Lysosomal pH measurement

20,000 cells were plated in black p96 plate with transparent bottom (#Rev. C/0815; PerkinElmer). A 2 mM LysoSensor Yellow/Blue dextran probe (#22460; Thermo Fisher Scientific) was added, and fluorescence was measured after 24 h in a Microplate Infinite Pro 200 reader (Tecan).

Proliferation assays

1,000 cells of parental and KO cells were seeded in XCelLigence plates in triplicates (#300600890; Agilent). Cells were treated with the corresponding treatment (i.e., either no glucose or no FBS) 24 h after seeding and measurements were taken every 6 min for 96 h. The area under the curve was calculated for data plotting.

T cell cytotoxicity experiments

Mouse CD8⁺ cells were isolated and purified from OTI mice spleens. OTI mice harbor a transgenic TCR recognizing the SIINFEKL peptide from ovalbumin on CD8⁺ T cells (InvivoGen; #vac-sin). Briefly, spleens were disaggregated in PBS and the cell suspension was filtered through a 40-µm cell strainer, erythrocytes were lysed with ACK lysis buffer (NH₄Cl, KHCO₃, EDTA Na.2H₂O, pH 7.4) and after washing, cells were resuspended in autoMACS buffer (25 mM EDTA, 1% FBS, 1% P/E) and isolated from the spleens using the MACS CD8⁺ T Cell Isolation Kit (#130-095-236; Miltenyi Biotec) following the manufacturer’s instructions. CD8⁺ OTI cells were activated using CD3/CD28 activator beads (#11452D; Thermo Fisher Scientific) one bead/two cells and 30 U/ml of hIL-2 (#CN70389; Novartis).

15,000 DSTYK KO or control LLC cells were seeded in XCeLLigence E-Plates 16 PET (#300600890; Agilent). Tumor cells were then stimulated with 50 U/ml mouse IFN-γ overnight and then pulsed with SIINFEKL peptide (JPT; 1 ng/ml) for an additional 4 h. LLC cells were washed and activated CD8⁺ OTI T cells were added on top at different tumor cell/T cell ratios. Tumor cell growth and cytotoxicity were measured overtime in an xCELLigence Real-Time Cell Analysis MP instrument (Agilent) for 96 h.

To study the toxic effect of TNF-α on our cells, a similar procedure was performed. 15,000 LLC or 10,000 H2009 cells were seeded. 24 h after cell seeding, 20 ng/ml of mouse TNF-α (#259411; Abcam) or human TNF-α (#9642; Abcam) were added to LCC or H2009, respectively, and the toxicity effects were measured for 96 h. Etanercept (Enbrel; Pfizer) was used to block TNF-α.

To modulate the autophagy pathway, plated cells were treated with 25 μM of chloroquine (#C6628; Sigma-Aldrich) or 300 nM of rapamycin (#R8781; Sigma-Aldrich) and 4 h later, 20 ng/ml of mouse TNF-α (#259411; Abcam), or human TNF-α (#9642; Abcam) were added to corresponding wells.

In vivo studies

All animal experiments were conducted in accordance with the protocols approved by the institutional animal care committee (references 049-18, 035c-20, and 037-19).

1 × 10⁶ LLC or 2 × 10⁶ UN-SCC680 were subcutaneously inoculated in one flank of 8-wk-old immunocompetent female C57BL/6J or A/J mice, respectively (Harlan-Winkelmann).

shRNAs were activated by adding doxycycline to mice drinking water when tumors reached a volume of 50–100 mm³. Tumor volume (weight² × length × 0.52) was measured with a digital caliper twice a week until sacrifice.

For tumor growth rate studies of mouse-derived cell lines, 3 × 10⁶ LLC, UN-SCC679 or UN-SCC680 cells were subcutaneously inoculated in both flanks of 8-wk-old female Rag^−/− IL2Rg^−/− mice (Harlan-Winkelmann).

Depletion of CD8, CD4 or natural killer cells was performed by intraperitoneal injection of 100 μg anti-mouse CD8a (clone 2.43; Bio X Cell), CD4 (clone GK1.5; BioXCell) or NK1.1 (clone PK136; Bio X Cell), respectively, at days 6, 10, 14, 18, 22, 26, and 30 after cell inoculation.

For sh#Dstyk + anti–PD-1 combination treatment, LLC tumor–bearing mice were treated when tumors reached 75–100 mm³ with 200 μg anti–PD-1 blocking antibody (#RMP1-14; Bio X Cell) intraperitoneally at days 6, 9, 12, and 15.

LLC tumor–bearing mice were intraperitoneally treated with 40 mg of etanercept (Enbrel; Pfizer) to block TNF-α at days 0, 2, 4, and 6 after inoculation.

hCD2RFP mice, used for intravital microscopy experiments were a kind gift from Mark Coles from the University of York, York, UK, and OTI mice were purchased from Jackson. Ages of mice included in experiments ranged from 8 to 12 wk.

Patient samples

Two series of patients were used. A series of frozen material available from 45 patients with NSCLC whose tumors underwent surgical resection at CIMA-CUN from 2000 to 2012 was evaluated. The inclusion criteria were NSCLC histology, stage I to III, no neoadjuvant or adjuvant chemotherapy or radiotherapy, and absence of cancer within the 5 yr prior to lung cancer surgery. A series of 76 patients from Vall d’Hebron hospital (VH), previously reported (Frigola et al., 2022), diagnosed with advanced NSCLC and treated with ICIs as monotherapy. 54 (70.1%) had adenocarcinoma histology, 70 (90.1%) were current or former smokers, and 48 (62.3%) were males. 62 (80.5%) were treated with ICIs as monotherapy. 30 (39%) and 34 (44.2%) patients were treated with ICIs in their first or second line of therapy, respectively, whereas 13 (16.9%) patients were treated in ≥3 line.

Statistics

Sample size was chosen based on similar experiments previously published by the authors. When possible, all experiments were reproduced a minimum of three times (independent biological replicates). For comparing two groups, samples normality (Shapiro–Wilk test) and variance (Levene test) were explored. Groups with a normal distribution were compared using a two-tailed t test. Non-normal samples were analyzed using a Mann–Whitney test (equal variances) or a median test (unequal variances).

Online supplemental material

Fig. S1 shows the percentage of patients with DSTYK alteration from 24 different cancer types. Fig. S2 shows validation of IF in microvesicles as well as confirmation of different molecular pathways resulted from RNAseq and immunoprecipitation studies. Fig. S3 shows no alteration in mitochondrial respiration under baseline conditions in an altered DSTYK context. Fig. S4 shows mitochondrial morphological and functional features in an altered DSTYK context. Fig. S5 describes DSTYK KO cell lines behavior in vitro and in vivo and shows their response to different agents. Finally, Fig. S5 pictures the role of DSTYK amplification in a non-tumoral context and the role of DSTYK mutation in a tumoral context. Table S1 summarizes CIMA-CUN cohort clinical data. Table S2 shows differentially expressed genes in mouse cells in an altered DSTYK context. Table S3 shows a list of genes co-precipitated with Flag-DSTYK in an immunoprecipitation experiment using LLC cells. Table S4 shows Western blot densitometry analysis. Table S5 shows antibody references and dilutions as well as primers sequences used along the work. Video 1 shows mitochondrial and lysosomal dynamics in DSTYK KO cells under metabolic stress. Video 2 shows intravital microscopy of T cell responses in LLC DSTYK deficient tumors.