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Review
. 2024 Jul 19:15:1414376.
doi: 10.3389/fimmu.2024.1414376. eCollection 2024.

Mismatch repair-proficient tumor footprints in the sands of immune desert: mechanistic constraints and precision platforms

Affiliations
Review

Mismatch repair-proficient tumor footprints in the sands of immune desert: mechanistic constraints and precision platforms

Biswanath Majumder et al. Front Immunol. .

Abstract

Mismatch repair proficient (MMRp) tumors of colorectal origin are one of the prevalent yet unpredictable clinical challenges. Despite earnest efforts, optimal treatment modalities have yet to emerge for this class. The poor prognosis and limited actionability of MMRp are ascribed to a low neoantigen burden and a desert-like microenvironment. This review focuses on the critical roadblocks orchestrated by an immune evasive mechanistic milieu in the context of MMRp. The low density of effector immune cells, their weak spatiotemporal underpinnings, and the high-handedness of the IL-17-TGF-β signaling are intertwined and present formidable challenges for the existing therapies. Microbiome niche decorated by Fusobacterium nucleatum alters the metabolic program to maintain an immunosuppressive state. We also highlight the evolving strategies to repolarize and reinvigorate this microenvironment. Reconstruction of anti-tumor chemokine signaling, rational drug combinations eliciting T cell activation, and reprograming the maladapted microbiome are exciting developments in this direction. Alternative vulnerability of other DNA damage repair pathways is gaining momentum. Integration of liquid biopsy and ex vivo functional platforms provide precision oncology insights. We illustrated the perspectives and changing landscape of MMRp-CRC. The emerging opportunities discussed in this review can turn the tide in favor of fighting the treatment dilemma for this elusive cancer.

Keywords: MMRp; colorectal cancer; functional platforms; gut microbiota; precision medicine; predictive biomarkers; therapeutic vulnerability; tumor immune microenvironment.

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Conflict of interest statement

BM, LM and NN are employees of Bugworks Research Inc. and hold shares of the company. SD is co-founder of Bugworks Research Inc and holds equities. BM serves as an honorary scientific advisor of Praesidia Biotherapeutics, Bangalore, India and a consultant of Aryastha Life Sciences, Hyderabad, India.

Figures

Figure 1
Figure 1
Tumor immune microenvironment of MMRp displays mechanistic constrains: potential strategies of reinvigorating. Despite representing more than three-fourths of the entire CRC population, the majority of MMRp CRC belongs to high-risk and poor prognoses. The TiME of CRC has multiple mechanistic barriers that hamper the therapy success. High TCR diversity and low TILs density in the margin and core at primary CRC sites are associated with desmoplastic stroma, growth-promoting oncogenic signaling, poor blood vessel density and patterns leading to oxygen and nutrients deprivation. Poor microbiome context and active involvement of Treg and MDSC in a traditionally low TMB milieu critically orchestrate immune evasion of disseminating tumor cells to distant sites through unguarded blood vessels and immunologically skewed TDLN’s surveillance. The phenotypic analysis of TILs confirms the presence of immune cell types of suppressive functions and corresponding cytokines and chemokine networks that protect the tumor from immune attacks. Several agonists and antagonists of chemokines, TGF-β-targeted therapy, and vaccines can act in concert with other strategies to reinvigorate and stabilize TILs and TLS via niche-specific recruitments of the anti-tumor immune army. Finally, augmenting neoantigen load and DC functionalities cross prime CD8+T cells. In totality, other immune and non-immune targets present in the TiME provide an opportunity to rationally target this challenging microenvironment in clinical settings and improve the response.
Figure 2
Figure 2
Comparative gut microbiome profiles in MMRp and non MMRp tumor hosts underline multiple contextual constraints and explain barriers to therapy success. The global loss of protective gut resident commensal bacteria makes the border porous for invading bacteria and supports their colonization. Different next-generation sequencing platforms and in silico analysis enable determining the high load of such bacteria and dissecting the loss of diversity in MMRp interface. This maladaptation promotes the metabolic bias in the microenvironment characterized by the overproduction of lactate, propionate, long-chain fatty acids and concomitant loss of glycans, short-chain fatty acids like butyrates, vitamins, amino acids, retinoic acids, and nucleic acids. In such conditions, intra-tumoral and intracellular bacteria facilitate the polarization of immune cells like MDSC, Treg and M2 macrophages, creating a suppressive paracrine cytokine loop. This polarization indicates a sharp contrast with MMRd, where a permissive metabolic footprint favors the preservation of cytokines like IL-12 and IFN-γ, bacterial antigen presentation by M1 macrophages. Under this condition, the interaction of bacterial LPS with TLR in macrophages triggers a signaling pathway via canonical myeloid differentiation primary response 88 (MyD88) and TIR domain-containing adaptor inducing interferon-β (TRIF) that engages IRFs and produces type 1 IFN. Fn-mediated altered cytokines and other anti-apoptotic mechanisms confer resistance by orchestrating an M1 toM2 paradigm shift. Macrophages (M1), CD8, and NK-mediated production of anti-tumor cytotoxic effectors like perforin (PFN) and granzyme-B (GzB) elicit tumor-killing effects. TGF-β, IL-10 and IL-17 impair immune-effector function in MMRp. Multiple strategies focusing on improving the hostile tumor-microbiome interface in MMRp can reverse the suppressive state. Adapted from “Keystone Gut Microbiota Species Provide Colonization Resistance to Invading Bacteria” by BioRender.com (2021). Retrieved from, https://app.biorender.com/biorender-templates.
Figure 3
Figure 3
Vulnerabilities and alternative actionabilities in MMRp tumors decipher the key biomarkers and molecular targets in DDR machinery. MMRp tumors efficiently bypass key base pair mismatches using a repair mechanism that recruits repair proteins in the recognition-activation-resynthesis-ligation cascade. Although MLH complex destabilization and PLOEed perturbation are key actionable areas, the limited options in this class of MMR system highlight the need to search for parallel alternative targets involved in base excision repair (BER), nucleotide excision repair (NER), homologous recombination (HR) and nonhomologous end joining (NHEJ). Biomarkers for each repair category are presented in boxes. Therapeutic targets and their perturbations are indicated in red. POLE/D1, PARP, ATM, ATR, and Chk are key targets for which drugs are either under clinical development or approved for one or more indications. ATR and concurrent radiation can act in synergy to induce STING-dependent IFN1 production, and deliver conditional lethal hits leading to the killing of the tumors. Key steps of molecular mechanisms are depicted in the figure and mentioned in corresponding boxes. MSH, MutS homologs; MLH, MutL protein homolog; PMS2, Postmeiotic segregation Increased 2; EXO1, exonuclease 1; RFC, Replication factor C; PCNA, proliferating cell nuclear antigen; POLε, DNA polymerase epsilon POLδ, polymerase delta; XP-F, xeroderma pigmentosum; ERCC1, excision repair cross-complementation group1; FMCD2, Fanconi anemia group D2; MRN, Mre11-Rad50-Nbs1.
Figure 4
Figure 4
Precision oncology molecular multi-omics and functional platforms in predicting recurrence, response and guiding rational combinations in MMRp. Information obtained from systematic and multilayered molecular profiling of patient tumors converging genomics, epigenomics and proteomics from a longitudinal analysis of liquid biopsy and clinical biopsied samples (fresh unfixed or fixed tissues) provide critical spatiotemporal dynamic contexts of biomarkers, signatures and tumor-immune interface. Finally, it helps predict the recurrence risk, including therapy-driven or therapy-independent recurrence and clonal expansion. Change in ctDNA levels in serum is a reliable predictor that informs about a prospective clinical recurrence and, therefore, opens a strategic window in guiding the treatment plan ahead of recurrence. Multiple synthetic lethality screens like CRISPER knockout and conditional lethality decipher the pathway dependency and oncogenic addictions for delineating the druggable targets (180). Functional prediction platforms led by microenvironment-guided drug sensitivity screens actively leverage information from contextually relevant phenotypic readouts in a mechanistic setting. This clinical avatar works in coordination with molecular oncology modalities where clinically meaningful evidence of actionability is available and can provide an alternative solution when such biomarker information is absent or not translatable. An integrative cross-functional approach uses multiple live systems covering 2D cell lines, 3D organoids and non-dissociated tumor slices depending on the requirements and availability. Mice models can still evaluate the systems-level modulation of drugs and their synergy. These models show the advantage of obtaining data from real-world diverse assays using live cultures focusing on drug reactivity and functional modulation patterns in time and space. The provision is there to integrate the outputs into a predictive score. The clinical relevance, speed and scalability are not uniform across the platforms. Microenvironment-guided selection of optimal therapy combination in trials led by such assay outputs takes informed decisions by integrating multi-omics and spatial biology context at single-cell levels. The platform-guided selection has the power to improve response rate and differentiate superior combinations and synergy.

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