Molecular cartography uncovers evolutionary and microenvironmental dynamics in sporadic colorectal tumors.

Colorectal cancer exhibits dynamic cellular and genetic heterogeneity during progression from precursor lesions toward malignancy. Analysis of spatial multi-omic data from 31 human colorectal specimens enabled phylogeographic mapping of tumor evolution that revealed individualized progression trajectories and accompanying microenvironmental and clonal alterations. Phylogeographic mapping ordered genetic events, classified tumors by their evolutionary dynamics, and placed clonal regions along global pseudotemporal progression trajectories encompassing the chromosomal instability (CIN+) and hypermutated (HM) pathways. Integrated single-cell and spatial transcriptomic data revealed recurring epithelial programs and infiltrating immune states along progression pseudotime. We discovered an immune exclusion signature (IEX), consisting of extracellular matrix regulators DDR1, TGFBI, PAK4, and DPEP1, that charts with CIN+ tumor progression, is associated with reduced cytotoxic cell infiltration, and shows prognostic value in independent cohorts. This spatial multi-omic atlas provides insights into colorectal tumor-microenvironment co-evolution, serving as a resource for stratification and targeted treatments.

Quantitative Proteomics of the Cancer Cell Line Encyclopedia.

Proteins are essential agents of biological processes. To date, large-scale profiling of cell line collections including the Cancer Cell Line Encyclopedia (CCLE) has focused primarily on genetic information whereas deep interrogation of the proteome has remained out of reach. Here, we expand the CCLE through quantitative profiling of thousands of proteins by mass spectrometry across 375 cell lines from diverse lineages to reveal information undiscovered by DNA and RNA methods. We observe unexpected correlations within and between pathways that are largely absent from RNA. An analysis of microsatellite instable (MSI) cell lines reveals the dysregulation of specific protein complexes associated with surveillance of mutation and translation. These and other protein complexes were associated with sensitivity to knockdown of several different genes. These data in conjunction with the wider CCLE are a broad resource to explore cellular behavior and facilitate cancer research.

Comprehensive mapping of cell fates in microsatellite unstable cancer cells supports dual targeting of WRN and ATR.

Addiction to the WRN helicase is a unique vulnerability of human cancers with high levels of microsatellite instability (MSI-H). However, while prolonged loss of WRN ultimately leads to cell death, little is known about how MSI-H cancers initially respond to acute loss of WRN-knowledge that would be helpful for informing clinical development of WRN targeting therapy, predicting possible resistance mechanisms, and identifying useful biomarkers of successful WRN inhibition. Here, we report the construction of an inducible ligand-mediated degradation system in which the stability of endogenous WRN protein can be rapidly and specifically tuned, enabling us to track the complete sequence of cellular events elicited by acute loss of WRN function. We found that WRN degradation leads to immediate accrual of DNA damage in a replication-dependent manner that curiously did not robustly engage checkpoint mechanisms to halt DNA synthesis. As a result, WRN-degraded MSI-H cancer cells accumulate DNA damage across multiple replicative cycles and undergo successive rounds of increasingly aberrant mitoses, ultimately triggering cell death. Of potential therapeutic importance, we found no evidence of any generalized mechanism by which MSI-H cancers could adapt to near-complete loss of WRN. However, under conditions of partial WRN degradation, addition of low-dose ATR inhibitor significantly increased their combined efficacy to levels approaching full inactivation of WRN. Overall, our results provide the first comprehensive view of molecular events linking upstream inhibition of WRN to subsequent cell death and suggest that dual targeting of WRN and ATR might be a useful strategy for treating MSI-H cancers.

Lynch syndrome-associated and sporadic microsatellite unstable colorectal cancers: different patterns of clonal evolution yield highly similar tumours.

Microsatellite unstable colorectal cancer (MSI-CRC) can arise through germline mutations in mismatch repair (MMR) genes in individuals with Lynch syndrome (LS), or sporadically through promoter methylation of the MMR gene MLH1. Despite the different origins of hereditary and sporadic MSI tumours, their genomic features have not been extensively compared. A prominent feature of MMR-deficient genomes is the occurrence of many indels in short repeat sequences, an understudied mutation type due to the technical challenges of variant calling in these regions. In this study, we performed whole genome sequencing and RNA-sequencing on 29 sporadic and 14 hereditary MSI-CRCs. We compared the tumour groups by analysing genome-wide mutation densities, microsatellite repeat indels, recurrent protein-coding variants, signatures of single base, doublet base, and indel mutations, and changes in gene expression. We show that the mutational landscapes of hereditary and sporadic MSI-CRCs, including mutational signatures and mutation densities genome-wide and in microsatellites, are highly similar. Only a low number of differentially expressed genes were found, enriched to interferon-γ regulated immune response pathways. Analysis of the variance in allelic fractions of somatic variants in each tumour group revealed higher clonal heterogeneity in sporadic MSI-CRCs. Our results suggest that the differing molecular origins of MMR deficiency in hereditary and sporadic MSI-CRCs do not result in substantial differences in the mutational landscapes of these tumours. The divergent patterns of clonal evolution between the tumour groups may have clinical implications, as high clonal heterogeneity has been associated with decreased tumour immunosurveillance and reduced responsiveness to immunotherapy.

Performance assessment of computational tools to detect microsatellite instability.

Microsatellite instability (MSI) is a phenomenon seen in several cancer types, which can be used as a biomarker to help guide immune checkpoint inhibitor treatment. To facilitate this, researchers have developed computational tools to categorize samples as having high microsatellite instability, or as being microsatellite stable using next-generation sequencing data. Most of these tools were published with unclear scope and usage, and they have yet to be independently benchmarked. To address these issues, we assessed the performance of eight leading MSI tools across several unique datasets that encompass a wide variety of sequencing methods. While we were able to replicate the original findings of each tool on whole exome sequencing data, most tools had worse receiver operating characteristic and precision-recall area under the curve values on whole genome sequencing data. We also found that they lacked agreement with one another and with commercial MSI software on gene panel data, and that optimal threshold cut-offs vary by sequencing type. Lastly, we tested tools made specifically for RNA sequencing data and found they were outperformed by tools designed for use with DNA sequencing data. Out of all, two tools (MSIsensor2, MANTIS) performed well across nearly all datasets, but when all datasets were combined, their precision decreased. Our results caution that MSI tools can have much lower performance on datasets other than those on which they were originally evaluated, and in the case of RNA sequencing tools, can even perform poorly on the type of data for which they were created.

Detecting microsatellite instability by length comparison of microsatellites in the 3' untranslated region with RNA-seq.

Microsatellite instability (MSI), a phenomenon caused by deoxyribonucleic acid (DNA) mismatch repair system deficiencies, is an important biomarker in cancer research and clinical diagnostics. MSI detection often involves next-generation sequencing data, with many studies focusing on DNA. Here, we introduce a novel approach by measuring microsatellite lengths directly from ribonucleic acid sequencing (RNA-seq) data and comparing its distribution to detect MSI. Our findings reveal distinct instability patterns between MSI-high (MSI-H) and microsatellite stable samples, indicating the efficacy of RNA-based MSI detection. Additionally, microsatellites in the 3'-untranslated regions showed the greatest predictive value for MSI detection. Notably, this efficacy extends to detecting MSI-H samples even in tumors not commonly associated with MSI. Our approach highlights the utility of RNA-seq data in MSI detection, facilitating more precise diagnostics through the integration of various biological data.

Current recommendations and recent progress in endometrial cancer.

Endometrial cancer is the most common gynecologic cancer in the United States, and its incidence is rising. Although there have been significant recent advances in our understanding of endometrial cancer biology, many aspects of treatment remain mired in controversy, including the role of surgical lymph node assessment and the selection of patients for adjuvant radiation or chemotherapy. For the subset of women with microsatellite-instable, metastatic disease, anti- programmed cell death protein 1 immunotherapy (pembrolizumab) is now approved by the US Food and Drug Administration, and numerous trials are attempting to build on this early success.

MSI-XGNN: an explainable GNN computational framework integrating transcription- and methylation-level biomarkers for microsatellite instability detection.

Microsatellite instability (MSI) is a hypermutator phenotype caused by DNA mismatch repair deficiency. MSI has been reported in various human cancers, particularly colorectal, gastric and endometrial cancers. MSI is a promising biomarker for cancer prognosis and immune checkpoint blockade immunotherapy. Several computational methods have been developed for MSI detection using DNA- or RNA-based approaches based on next-generation sequencing. Epigenetic mechanisms, such as DNA methylation, regulate gene expression and play critical roles in the development and progression of cancer. We here developed MSI-XGNN, a new computational framework for predicting MSI status using bulk RNA-sequencing and DNA methylation data. MSI-XGNN is an explainable deep learning model that combines a graph neural network (GNN) model to extract features from the gene-methylation probe network with a CatBoost model to classify MSI status. MSI-XGNN, which requires tumor-only samples, exhibited comparable performance with two well-known methods that require tumor-normal paired sequencing data, MSIsensor and MANTIS and better performance than several other tools. MSI-XGNN also showed good generalizability on independent validation datasets. MSI-XGNN identified six MSI markers consisting of four methylation probes (EPM2AIP1|MLH1:cg14598950, EPM2AIP1|MLH1:cg27331401, LNP1:cg05428436 and TSC22D2:cg15048832) and two genes (RPL22L1 and MSH4) constituting the optimal feature subset. All six markers were significantly associated with beneficial tumor microenvironment characteristics for immunotherapy, such as tumor mutation burden, neoantigens and immune checkpoint molecules such as programmed cell death-1 and cytotoxic T-lymphocyte antigen-4. Overall, our study provides a powerful and explainable deep learning model for predicting MSI status and identifying MSI markers that can potentially be used for clinical MSI evaluation.

Deciphering gene contributions and etiologies of somatic mutational signatures of cancer.

Somatic mutational signatures (MSs) identified by genome sequencing play important roles in exploring the cause and development of cancer. Thus far, many such signatures have been identified, and some of them do imply causes of cancer. However, a major bottleneck is that we do not know the potential meanings (i.e. carcinogenesis or biological functions) and contributing genes for most of them. Here, we presented a computational framework, Gene Somatic Genome Pattern (GSGP), which can decipher the molecular mechanisms of the MSs. More importantly, it is the first time that the GSGP is able to process MSs from ribonucleic acid (RNA) sequencing, which greatly extended the applications of both MS analysis and RNA sequencing (RNAseq). As a result, GSGP analyses match consistently with previous reports and identify the etiologies for a number of novel signatures. Notably, we applied GSGP to RNAseq data and revealed an RNA-derived MS involved in deficient deoxyribonucleic acid mismatch repair and microsatellite instability in colorectal cancer. Researchers can perform customized GSGP analysis using the web tools or scripts we provide.

Characterization of discordance between mismatch repair deficiency and microsatellite instability testing may prevent inappropriate treatment with immunotherapy.

In the Drug Rediscovery Protocol (DRUP), patients with cancer are treated based on their tumor molecular profile with approved targeted and immunotherapies outside the labeled indication. Importantly, patients undergo a tumor biopsy for whole-genome sequencing (WGS) which allows for a WGS-based evaluation of routine diagnostics. Notably, we observed that not all biopsies of patients with dMMR/MSI-positive tumors as determined by routine diagnostics were classified as microsatellite-unstable by subsequent WGS. Therefore, we aimed to evaluate the discordance rate between routine dMMR/MSI diagnostics and WGS and to further characterize discordant cases. We assessed patients enrolled in DRUP with dMMR/MSI-positive tumors identified by routine diagnostics, who were treated with immune checkpoint blockade (ICB) and for whom WGS data were available. Patient and tumor characteristics, study treatment outcomes, and material from routine care were retrieved from the patient medical records and via Palga (the Dutch Pathology Registry), and were compared with WGS results. Initially, discordance between routine dMMR/MSI diagnostics and WGS was observed in 13 patients (13/121; 11%). The majority of these patients did not benefit from ICB (11/13; 85%). After further characterization, we found that in six patients (5%) discordance was caused by dMMR tumors that did not harbor an MSI molecular phenotype by WGS. In six patients (5%), discordance was false due to the presence of multiple primary tumors (n = 3, 2%) and misdiagnosis of dMMR status by immunohistochemistry (n = 3, 2%). In one patient (1%), the exact underlying cause of discordance could not be identified. Thus, in this group of patients limited to those initially diagnosed with dMMR/MSI tumors by current routine diagnostics, the true assay-based discordance rate between routine dMMR/MSI-positive diagnostics and WGS was 5%. To prevent inappropriate ICB treatment, clinicians and pathologists should be aware of the risk of multiple primary tumors and the limitations of different tests. © 2024 The Pathological Society of Great Britain and Ireland.

The aminophospholipid transporter, ATP8B3, as a potential biomarker and target for enhancing the therapeutic effect of PD-L1 blockade in colon adenocarcinoma.

BACKGROUND: Colon adenocarcinoma (COAD) is a prevalent malignant tumor globally, contributing significantly to cancer-related mortality. COAD guidelines label MSI (Microsatellite instability) and MSS (Microsatellite stability) subtypes as global classification criteria and treatment strategy selection criteria for COAD. Various combination therapies involving PD-L1 inhibitors and adjuvant therapy to enhance anti-tumor efficacy. METHODS: Datasets from single-cell RNA sequencing and bulk RNA sequencing in the TCGA and GEO databases were utilized to identify differentially expressed genes (DEGs). Furthermore, the correlation between ATP8B3 and PD-L1 was validated using siRNA, shRNA, and western blot analysis. Additionally, the association between ATP8B3 and immune checkpoint blockade (ICB) therapy was investigated through immune infiltration analysis and flow cytometry in both in vivo and in vitro assays. RESULTS: In the COAD patient group, ATP8B3 significantly contributed to the establishment of an immunosuppressive microenvironment. Inhibiting ATP8B3 led to a reduction in PD-L1 expression in colon cancer cell lines. Additionally, ATP8B3 expression levels could serve as a potential guide for PD-L1 treatment in MSI-H COAD patients, with higher ATP8B3 expression associated with increased sensitivity to PD-L1 therapy. However, due to the lack of immuno-killer cells in the microenvironment of MSS subtypes, elevated ATP8B3 expression couldn't increase the sensitivity of MSS COAD patients to PD-L1 inhibitors. CONCLUSION: Our research results support that Inhibiting ATP8B3 could enhance TIL (tumor-infiltrating lymphocyte) infiltration by reducing PD-L1 expression in MSI-H COAD, thereby serving as an effective strategy to improve PD-L1 blocker efficacy. The treatment strategy of combining ATP8B3 inhibitors and immunotherapy for MSI/MSS COAD patients will be the best choice.

One label is all you need: Interpretable AI-enhanced histopathology for oncology.

Artificial Intelligence (AI)-enhanced histopathology presents unprecedented opportunities to benefit oncology through interpretable methods that require only one overall label per hematoxylin and eosin (H&E) slide with no tissue-level annotations. We present a structured review of these methods organized by their degree of verifiability and by commonly recurring application areas in oncological characterization. First, we discuss morphological markers (tumor presence/absence, metastases, subtypes, grades) in which AI-identified regions of interest (ROIs) within whole slide images (WSIs) verifiably overlap with pathologist-identified ROIs. Second, we discuss molecular markers (gene expression, molecular subtyping) that are not verified via H&E but rather based on overlap with positive regions on adjacent tissue. Third, we discuss genetic markers (mutations, mutational burden, microsatellite instability, chromosomal instability) that current technologies cannot verify if AI methods spatially resolve specific genetic alterations. Fourth, we discuss the direct prediction of survival to which AI-identified histopathological features quantitatively correlate but are nonetheless not mechanistically verifiable. Finally, we discuss in detail several opportunities and challenges for these one-label-per-slide methods within oncology. Opportunities include reducing the cost of research and clinical care, reducing the workload of clinicians, personalized medicine, and unlocking the full potential of histopathology through new imaging-based biomarkers. Current challenges include explainability and interpretability, validation via adjacent tissue sections, reproducibility, data availability, computational needs, data requirements, domain adaptability, external validation, dataset imbalances, and finally commercialization and clinical potential. Ultimately, the relative ease and minimum upfront cost with which relevant data can be collected in addition to the plethora of available AI methods for outcome-driven analysis will surmount these current limitations and achieve the innumerable opportunities associated with AI-driven histopathology for the benefit of oncology.

COSAP: Comparative Sequencing Analysis Platform.

BACKGROUND: Recent improvements in sequencing technologies enabled detailed profiling of genomic features. These technologies mostly rely on short reads which are merged and compared to reference genome for variant identification. These operations should be done with computers due to the size and complexity of the data. The need for analysis software resulted in many programs for mapping, variant calling and annotation steps. Currently, most programs are either expensive enterprise software with proprietary code which makes access and verification very difficult or open-access programs that are mostly based on command-line operations without user interfaces and extensive documentation. Moreover, a high level of disagreement is observed among popular mapping and variant calling algorithms in multiple studies, which makes relying on a single algorithm unreliable. User-friendly open-source software tools that offer comparative analysis are an important need considering the growth of sequencing technologies. RESULTS: Here, we propose Comparative Sequencing Analysis Platform (COSAP), an open-source platform that provides popular sequencing algorithms for SNV, indel, structural variant calling, copy number variation, microsatellite instability and fusion analysis and their annotations. COSAP is packed with a fully functional user-friendly web interface and a backend server which allows full independent deployment for both individual and institutional scales. COSAP is developed as a workflow management system and designed to enhance cooperation among scientists with different backgrounds. It is publicly available at https://cosap.bio and https://github.com/MBaysanLab/cosap/ . The source code of the frontend and backend services can be found at https://github.com/MBaysanLab/cosap-webapi/ and https://github.com/MBaysanLab/cosap_frontend/ respectively. All services are packed as Docker containers as well. Pipelines that combine algorithms can be customized and new algorithms can be added with minimal coding through modular structure. CONCLUSIONS: COSAP simplifies and speeds up the process of DNA sequencing analyses providing commonly used algorithms for SNV, indel, structural variant calling, copy number variation, microsatellite instability and fusion analysis as well as their annotations. COSAP is packed with a fully functional user-friendly web interface and a backend server which allows full independent deployment for both individual and institutional scales. Standardized implementations of popular algorithms in a modular platform make comparisons much easier to assess the impact of alternative pipelines which is crucial in establishing reproducibility of sequencing analyses.

An Innovative and Accurate Next-Generation Sequencing-Based Microsatellite Instability Detection Method for Colorectal and Endometrial Tumors.

The detection of microsatellite instability (MSI) and mismatch repair (MMR) deficiency has become mandatory for most tumors in recent years, owing to the development of immune checkpoint inhibitors as a highly effective therapy for MMR deficiency/MSI tumors. The timely and efficient detection of MSI is valuable, and new methods are increasingly being developed. To date, MMR assessment has been performed using immunohistochemistry of the 4 MMR proteins and/or microsatellite stability/MSI using PCR, mostly using the pentaplex panel. The implementation of next-generation sequencing (NGS) for MSI analysis would improve the effectiveness at a lower cost and in less time. This study describes the development of 8 new microsatellites combined with a classification algorithm, termed "Octaplex CaBio-MSID" (for Cancérologie Biologique MSI Detection tool), to assess MSI using NGS. A series of 303 colorectal cancer and 88 endometrial cancer samples were assessed via MSI testing using NGS using the Octaplex CaBio-MSID algorithm. The sensitivity and specificity of Octaplex CaBio-MSID were 98.4% and 98.4% for colorectal cancers, and 89.3% and 100% for endometrial cancers, respectively. This new NGS-based MSI detection method outperforms previously published methods (ie, Idylla [Biocartis], OncoMate MSI Dx [Promega], and Foundation One CDx [Roche Foundation Medicine]). Although highly efficient, Octaplex CaBio-MSID requires validation in a larger independent series of different tumor types.

Prognosis and immunotherapy efficacy in dMMR&MSS colorectal cancer patients and an MSI status predicting model.

The inconsistency between mismatch repair (MMR) protein immunohistochemistry (IHC) and microsatellite instability PCR (MSI-PCR) methods has been widely reported. We aim to investigate the prognosis and the effect of immunotherapy in dMMR by IHC but MSS by MSI-PCR (dMMR&MSS) colorectal cancer (CRC) patients. A microsatellite instability (MSI) predicting model was established to help find dMMR&MSS patients. MMR and MSI states were detected by the IHC and MSI-PCR in 1622 CRC patients (ZS6Y-1 cohort). Logistic regression analysis was used to screen clinical features to construct an MSI-predicting nomogram. We propose a new nomogram-based assay to find patients with dMMR&MSS, in which the MSI-PCR assay only detects dMMR patients with MSS predictive results. We applied the new strategy to a random cohort of 248 CRC patients (ZS6Y-2 cohort). The consistency of MMR IHC and MSI-PCR in the ZS6Y-1 cohort was 95.7% (1553/1622). Both pMMR&MSS and dMMR&MSS groups experienced significantly shorter overall survival (OS) than those in dMMR by IHC and MSI-H by MSI-PCR (dMMR&MSI-H) group (hazard ratio [HR] = 2.429, 95% confidence interval [CI]: 1.89-3.116, p < .01; HR = 21.96, 95% CI: 7.24-66.61, p < .01). The dMMR&MSS group experienced shorter OS than the pMMR&MSS group, but the difference did not reach significance (log rank test, p = .0686). In the immunotherapy group, the progression-free survival of dMMR&MSS patients was significantly shorter than that of dMMR&MSI-H patients (HR = 13.83, 95% CI: 1.508-126.8, p < .05). The ZS6Y-MSI-Pre nomogram (C-index = 0.816, 95% CI: 0.792-0.841, already online) found 66% (2/3) dMMR&MSS patients in the ZS6Y-2 cohort. There are significant differences in OS and immunotherapy effect between dMMR&MSI-H and dMMR&MSS patients. Our prediction model provides an economical way to screen dMMR&MSS patients.

Approaches for Lynch syndrome screening and characteristics of subtypes with mismatch repair deficiency in patients with colorectal carcinoma.

To evaluate different Lynch syndrome (LS) screening approaches and establish an efficient and sensitive strategy are critical for clinical practice. In total, 583 patients with colorectal carcinoma (CRC) at Fudan University Shanghai Cancer Center were enrolled. Patient samples were examined by immunohistochemistry (IHC) and next-generation sequencing (NGS), and MLH1 promoter hypermethylation (MPH) was detected in MLH1-deficient cases. Germline genetic testing was performed in cases with deleterious variants and large genomic rearrangements (LGRs) of tumor MMR genes were detected in cases with dMMR or MSI-H cases with no MMR germline variants. Our results showed that triage with IHC and followed by BRAF/MLH1 methylation testing (Strategy 1) identified 93.3% (70/75) of LS cases. IHC followed by germline NGS (Strategy 2) or direct tumor NGS (Strategy 3) both identified 98.7% (74/75) of LS cases. The proportion of LGRs in LS cases was 16.0% (12/75), while 84.0% (63/75) showed SNV/Indel. The average cost per patient was ¥6010.81, ¥6058.48, and ¥8029.98 for Strategy 1, Strategy 2 and Strategy 3, respectively. The average time spent on different strategies was 4.74 days (Strategy 1), 4.89 days (Strategy 2), and 14.50 days (Strategy 3) per patient, respectively. LS and Lynch-like syndrome (LLS) were associated with an earlier onset age than MPH. In conclusion, we compared different workflows for LS screening and IHC plus germline NGS is recommended for LS screening when taking sensitivity, time, and cost into account. Moreover, multiplex ligation-dependent probe amplification made up for the shortcoming of NGS and should be incorporated into routine screening.

Association of KRAS G12C Status with Age at Onset of Metastatic Colorectal Cancer.

The association of age at the onset of CRC and the prevalence of a KRAS G12C mutation is unclear. A retrospective, multicenter study evaluating metastatic CRC patients from January 2019 to July 2023, treated at the Oncoclinicas units and tested for tissue based KRAS/NRAS and BRAF mutations in a centralized genomics lab. A mismatch repair (MMR) status was retrieved from different labs and electronic medical records, as were patient demographics (age, gender) and tumor sidedness. The chi-square test was used to examine the association between clinical and molecular variables, with p value < 0.05 being statistically significant. A total of 858 cases were included. The median age was 63.7 years (range 22-95) and 17.4% were less than 50 years old at the diagnosis of metastatic CRC. Male patients represented 50.3% of the population. The sidedness distribution was as follows: left side 59.2%, right side 36.8% and not specified 4%. The prevalence of the KRAS mutation was 49.4% and the NRAS mutation was 3.9%. Among KRAS mutated tumors, the most common variants were G12V (27.6%) and G12D (23.5%), while KRAS G12C was less frequent (6.4%), which represented 3.1% of the overall population. The BRAF mutant cases were 7.3% and most commonly V600E. Only five (<1%) non-V600E mutations were detected. MSI-high or dMMR was present in 14 cases (1.6%). In the age-stratified analysis, left-sidedness (p < 0.001) and a KRAS G12C mutation (p = 0.046) were associated with a younger age (<50 years). In the sidedness-stratified analysis, a BRAF mutation (p = 0.001) and MSI-high/dMMR status (p = 0.009) were more common in right-sided tumors. Our data suggest that KRAS G12C mutations are more frequent in early-onset metastatic CRC. To the best of our knowledge, this is the largest cohort in the Latin American population with metastatic CRC reporting RAS, BRAF and MSI/MMR status.

Clinical and Genetic Characteristics of Early and Advanced Gastric Cancer.

Gastric cancer (GC) persists as the fourth most prevalent cause of global cancer-related mortality, presenting a challenge due to the scarcity of available therapeutic strategies. Precision medicine is crucial not only in the treatment but also in the management of GC. We performed gene panel sequencing with Oncomine focus assay comprising 52 cancer-associated genes and MSI analysis in 100 case-matched gastric cancer cases. A comprehensive analysis of clinical and genetic characteristics was conducted on these genetic results and clinicopathological findings. Upon comparison of clinicopathological characteristics, significant differences between early gastric cancer (EGC) and advanced gastric cancer (AGC) were observed in tumor location (p = 0.003), Lauren classification (p = 0.015), T stage (p = 0.000), and N stage (p = 0.015). The six most frequently mutated genes were PIK3CA (29%, 10/35), ERBB2 (17%, 6/35), KRAS (14%, 5/35), ALK (6%, 2/35), ESR1 (6%, 2/35), and FGFR3 (6%, 2/35). Regarding genetic variation, there was a tendency for the N stage to be higher in GC patients with mutated genes (p = 0.014). The frequency of mutations in GC patients was statistically significantly higher in AGC (n = 24) compared to EGC (n = 11) (odds ratio, 2.792; 95% confidence interval, 1.113 to 7.007; p = 0.026). Six of the ten GC patients carrying mutated genes and exhibiting MSI were classified into intestinal-type and undifferentiated GC, with the location of the tumor being in the lower-third. Among these patients, five harbored mutated PIK3CA, while the remaining patient had a mutation in ALK. Conclusions: AGC patients more frequently exhibited alterations of PIK3CA, KRAS, and ERBB2 as somatic oncogenic drivers, and displayed a higher prevalence of cumulative genetic events, including increased rates of PIK3CA mutations, enhanced detection of immunotherapy biomarkers, and mutations of the ESR1 gene.

Japanese Society of Medical Oncology clinical guidelines: Molecular testing for colorectal cancer treatment, 5th edition.

Molecular testing to determine optimal therapies is essential for managing patients with colorectal cancer (CRC). In October 2022, the Japanese Society of Medical Oncology published the 5th edition of the Molecular Testing Guideline for Colorectal Cancer Treatment. In this guideline, in patients with unresectable CRC, RAS/BRAF V600E mutational and mismatch repair tests are strongly recommended prior to first-line chemotherapy to select optimal first- and second-line therapies. In addition, HER2 testing is strongly recommended because the pertuzumab plus trastuzumab combination is insured after fluoropyrimidine, oxaliplatin, and irinotecan in Japan. Circulating tumor DNA (ctDNA)-based RAS testing is also strongly recommended to assess the indications for the readministration of anti-EGFR antibodies. Both tissue- and ctDNA-based comprehensive genomic profiling tests are strongly recommended to assess the indications for targeted molecular drugs, although they are currently insured in patients with disease progression after receiving standard chemotherapy (or in whom disease progression is expected in the near future). Mutational and mismatch repair testing is strongly recommended for patients with resectable CRC, and RAS/BRAF V600E mutation testing is recommended to estimate the risk of recurrence. Mutational and mismatch repair and BRAF testing are also strongly recommended for screening for Lynch syndrome. Circulating tumor DNA-based minimal residual disease (MRD) testing is strongly recommended for estimating the risk of recurrence based on clinical evidence, although MRD testing was not approved in Japan at the time of the publication of this guideline.

Microsatellite instability: A 2024 update.

Deficient mismatch repair (dMMR) results in microsatellite instability (MSI), a pronounced mutator phenotype. High-frequency MSI (MSI-H)/dMMR is gaining increasing interest as a biomarker for advanced cancer patients to determine their eligibility for immune checkpoint inhibitors (ICIs). Various methods based on next-generation sequencing (NGS) have been developed to assess the MSI status. Comprehensive genomic profiling (CGP) testing can precisely ascertain the MSI status as well as genomic alterations in a single NGS test. The MSI status can be also ascertained through the liquid biopsy-based CGP assays. MSI-H has thus been identified in various classes of tumors, resulting in a greater adoption of immunotherapy, which is hypothesized to be effective against malignancies that possess a substantial number of mutations and/or neoantigens. NGS-based studies have also characterized MSI-driven carcinogenesis, including significant rates of fusion kinases in colorectal cancers (CRCs) with MSI-H that are targets for therapeutic kinase inhibitors, particularly in MLH1-methylated CRCs with wild-type KRAS/BRAF. NTRK fusion is linked to the colorectal serrated neoplasia pathway. Recent advances in investigations of MSI-H malignancies have resulted in the development of novel diagnostic or therapeutic techniques, such as a synthetic lethal therapy that targets the Werner gene. DNA sensing in cancer cells is required for antitumor immunity induced by dMMR, opening up novel avenues and biomarkers for immunotherapy. Therefore, clinical relevance exists for analyses of MSI and MSI-H-associated genomic alterations in malignancy. In this article, we provide an update on MSI-driven carcinogenesis, with an emphasis on unique landscapes of diagnostic and immunotherapeutic strategies.