Deep sequencing and pathway-focused analysis revealed multigene oncodriver signatures predicting survival outcomes in advanced colorectal cancer

High-throughput sequencing and in-silico analysis confirm pathogenicity of novel MSH3 variants in African American colorectal cancer

The maintenance of DNA sequence integrity is critical to avoid accumulation of cancer-causing mutations. Inactivation of DNA Mismatch Repair (MMR) genes (e.g., MLH1 and MSH2) is common among many cancers, including colorectal cancer (CRC) and is the driver of classic microsatellite instability (MSI) in tumors. Somatic MSH3 alterations have been linked to a specific form of MSI called elevated microsatellite alterations at selected tetranucleotide repeats (EMAST) that is associated with patient poor prognosis and elevated among African American (AA) rectal cancer patients. Genetic variants of MSH3 and their pathogenicity vary among different populations, such as among AA, which are not well-represented in publicly available databases. Targeted exome sequencing of MSH3 among AA CRC samples followed by computational bioinformatic pipeline and molecular dynamic simulation analysis approach confirmed six identified MSH3 variants (c.G1237A, c.C2759T, c.G1397A, c.G2926A, c.C3028T, c.G3241A) that corresponded to MSH3 amino-acid changes (p.E413K; p.S466N; p.S920F; p.E976K; p.H1010Y; p.E1081K). All identified MSH3 variants were non-synonymous, novel, pathogenic, and show loss or gain of hydrogen bonding, ionic bonding, hydrophobic bonding, and disulfide bonding and have a deleterious effect on the structure of MSH3 protein. Some variants were located within the ATPase site of MSH3, affecting ATP hydrolysis that is critical for MSH3's function. Other variants were in the MSH3-MSH2 interacting domain, important for MSH3's binding to MSH2. Overall, our data suggest that these variants among AA CRC patients affect the function of MSH3 making them pathogenic and likely contributing to the development or advancement of CRC among AA. Further clarifying functional studies will be necessary to fully understand the impact of these variants on MSH3 function and CRC development in AA patients.

Oncotherapeutic Strategies in Early Onset Colorectal Cancer

Early onset colorectal cancer (EOCRC), defined as colorectal cancers in patients aged less than 50 years, is becoming an increasingly common issue, globally. Since 1994, the incidence of this condition has been rising by 2% annually. Approximately one in five patients under 50 years of age diagnosed with colorectal cancer have an underlying genetic predisposition syndrome. The detection of cancer among the other 80% of patients poses a considerable task, as there is no family history to advocate for commencing early screening in this group. Patients with EOCRC have distinct social, spiritual, fertility, and financial needs from their older counterparts that need to be addressed. This review discusses the risk factors associated with the development of EOCRC and current best practice for the management of this disease.

An integrative in-silico analysis discloses a novel molecular subset of colorectal cancer possibly eligible for immune checkpoint immunotherapy

BACKGROUND

Historically, the molecular classification of colorectal cancer (CRC) was based on the global genomic status, which identified microsatellite instability in mismatch repair (MMR) deficient CRC, and chromosomal instability in MMR proficient CRC. With the introduction of immune checkpoint inhibitors, the microsatellite and chromosomal instability classification regained momentum as the microsatellite instability condition predicted sensitivity to immune checkpoint inhibitors, possibly due to both high tumor mutation burden (TMB) and high levels of infiltrating lymphocytes. Conversely, proficient MMR CRC are mostly resistant to immunotherapy. To better understand the relationship between the microsatellite and chromosomal instability classification, and eventually discover additional CRC subgroups relevant for therapeutic decisions, we developed a computational pipeline that include molecular integrative analysis of genomic, epigenomic and transcriptomic data.

RESULTS

The first step of the pipeline was based on unsupervised hierarchical clustering analysis of copy number variations (CNVs) versus hypermutation status that identified a first CRC cluster with few CNVs enriched in Hypermutated and microsatellite instability samples, a second CRC cluster with a high number of CNVs mostly including non-HM and microsatellite stable samples, and a third cluster (7.8% of the entire dataset) with low CNVs and low TMB, which shared clinical-pathological features with Hypermutated CRCs and thus defined Hypermutated-like CRCs. The mutational features, DNA methylation profile and base substitution fingerprints of these tumors revealed that Hypermutated-like patients are molecularly distinct from Hypermutated and non-Hypermutated tumors and are likely to develop and progress through different genetic events. Transcriptomic analysis highlighted further differences amongst the three groups and revealed an inflamed tumor microenvironment and modulation Immune Checkpoint Genes in Hypermutated-like CRCs.

CONCLUSION

Therefore, our work highlights Hypermutated-like tumors as a distinct and previously unidentified CRC subgroup possibly responsive to immune checkpoint inhibitors. If further validated, these findings can lead to expanding the fraction of patients eligible to immunotherapy.

The Wnt signaling pathway in tumorigenesis, pharmacological targets, and drug development for cancer therapy

Wnt signaling was initially recognized to be vital for tissue development and homeostasis maintenance. Further studies revealed that this pathway is also important for tumorigenesis and progression. Abnormal expression of signaling components through gene mutation or epigenetic regulation is closely associated with tumor progression and poor prognosis in several tissues. Additionally, Wnt signaling also influences the tumor microenvironment and immune response. Some strategies and drugs have been proposed to target this pathway, such as blocking receptors/ligands, targeting intracellular molecules, beta-catenin/TCF4 complex and its downstream target genes, or tumor microenvironment and immune response. Here we discuss the roles of these components in Wnt signaling pathway in tumorigenesis and cancer progression, the underlying mechanisms that is responsible for the activation of Wnt signaling, and a series of drugs targeting the Wnt pathway provide multiple therapeutic values. Although some of these drugs exhibit exciting anti-cancer effect, clinical trials and systematic evaluation should be strictly performed along with multiple-omics technology.

A multidisciplinary approach for the differential diagnosis between multiple primary lung adenocarcinomas and intrapulmonary metastases

PURPOSE

The distinction between multiple primary lung cancers (MPLCs) and intrapulmonary metastases has a significant impact on tumor staging and therapeutic choices. Several criteria have been proposed to solve this diagnostic issue, but a definitive consensus is still missing. We tested the efficacy of a combined clinical, histopathological and molecular ("real world") approach for the correct classification of multiple lung tumors in a selected cohort of patients.

METHODS

24 multiple lung tumors with a diagnosis of adenocarcinoma from 10 patients were retrospectively reviewed. Radiological, pathological and clinical information, including follow-up, were integrated with molecular profiling via a routine multigene panel sequencing.

RESULTS

Comprehensive histologic assessment revealed readily distinguishable histologic patterns between multiple tumors suggesting unrelated lesions in 7 cases, in agreement with clinical, radiological and molecular data, thus leading to final diagnosis of MPLCs. In the remaining 3 cases, the differential diagnosis between MPLCs and intrapulmonary metastases was challenging, since the histologic features of the lesions were similar or identical. The final interpretation (2 MPLCs and 1 most likely intrapulmonary metastases) was reached thanks to the integration of all available data, and was confirmed by follow-up.

CONCLUSIONS

A multidisciplinary approach including a routinely affordable multigene panel sequencing is a useful tool to discriminate MPLCs from intrapulmonary metastases in multiple lung nodules sharing the adenocarcinoma histotype.

Clinical Multigene Panel Sequencing Identifies Distinct Mutational Association Patterns in Metastatic Colorectal Cancer

Extensive molecular characterization of human colorectal cancer (CRC) via Next Generation Sequencing (NGS) indicated that genetic or epigenetic dysregulation of a relevant, but limited, number of molecular pathways typically occurs in this tumor. The molecular picture of the disease is significantly complicated by the frequent occurrence of individually rare genetic aberrations, which expand tumor heterogeneity. Inter- and intratumor molecular heterogeneity is very likely responsible for the remarkable individual variability in the response to conventional and target-driven first-line therapies, in metastatic CRC (mCRC) patients, whose median overall survival remains unsatisfactory. Implementation of an extensive molecular characterization of mCRC in the clinical routine does not yet appear feasible on a large scale, while multigene panel sequencing of most commonly mutated oncogene/oncosuppressor hotspots is more easily achievable. Here, we report that clinical multigene panel sequencing performed for anti-EGFR therapy predictive purposes in 639 formalin-fixed paraffin-embedded (FFPE) mCRC specimens revealed previously unknown pairwise mutation associations and a high proportion of cases carrying actionable gene mutations. Most importantly, a simple principal component analysis directed the delineation of a new molecular stratification of mCRC patients in eight groups characterized by non-random, specific mutational association patterns (MAPs), aggregating samples with similar biology. These data were validated on a The Cancer Genome Atlas (TCGA) CRC dataset. The proposed stratification may provide great opportunities to direct more informed therapeutic decisions in the majority of mCRC cases.

A Simplified Genomic Profiling Approach Predicts Outcome in Metastatic Colorectal Cancer

The response of metastatic colorectal cancer (mCRC) to the first-line conventional combination therapy is highly variable, reflecting the elevated heterogeneity of the disease. The genetic alterations underlying this heterogeneity have been thoroughly characterized through omic approaches requiring elevated efforts and costs. In order to translate the knowledge of CRC molecular heterogeneity into a practical clinical approach, we utilized a simplified Next Generation Sequencing (NGS) based platform to screen a cohort of 77 patients treated with first-line conventional therapy. Samples were sequenced using a panel of hotspots and targeted regions of 22 genes commonly involved in CRC. This revealed 51 patients carrying actionable gene mutations, 22 of which carried druggable alterations. These mutations were frequently associated with additional genetic alterations. To take into account this molecular complexity and assisted by an unbiased bioinformatic analysis, we defined three subgroups of patients carrying distinct molecular patterns. We demonstrated these three molecular subgroups are associated with a different response to first-line conventional combination therapies. The best outcome was achieved in patients exclusively carrying mutations on TP53 and/or RAS genes. By contrast, in patients carrying mutations in any of the other genes, alone or associated with mutations of TP53/RAS, the expected response is much worse compared to patients with exclusive TP53/RAS mutations. Additionally, our data indicate that the standard approach has limited efficacy in patients without any mutations in the genes included in the panel. In conclusion, we identified a reliable and easy-to-use approach for a simplified molecular-based stratification of mCRC patients that predicts the efficacy of the first-line conventional combination therapy.