Microsatellite instability: a review of what the oncologist should know

Performance of the Idylla microsatellite instability test in endometrial cancer

CONTEXT

DNA mismatch repair (MMR) deficiency (dMMR) testing is now recommended in endometrial cancer. Defect identification in the molecules participating in this pathway, or the presence of microsatellite instability, are commonly employed for this purpose. Novel methods are continuously evolving to report dMMR/microsatellite instability and to easily perform routine diagnoses.

OBJECTIVE

The main aim of this study was to compare the concordance of the Idylla microsatellite instability test for the identification of dMMR endometrial cancer samples defined by immunohistochemistry and MMR genomic status.

DESIGN

We applied the Idylla MSI test to 126 early-stage endometrial cancer cases with MMR testing by immunohistochemistry and genomic characterization (methylation in MLH1 and sequence alterations in MLH1, PMS2, MSH2 and MSH6). Individual markers and overall specific performance indicators were explored.

RESULTS

The Idylla platform achieved a higher global concordance rate with MMR genomic status than with immunohistochemistry (75 % and 66 %, respectively). Sensitivity and specificity are also higher (75 % vs 66 % and 96 % vs 90 %, respectively). Clustering analysis split the patients into 2 well-differentiated clusters, the pMMR and the dMMR group, represented by MLH1/PMS2 loss and the MLH1 methylated promoter. Overall, immunohistochemistry and MMR genomic status identified more dMMR cases than did the Idylla test, although correlations were improved with a modified Idylla test cut-off.

CONCLUSIONS

Performance of the Idylla test was better correlated with MMR genomic status than MMR immunohistochemistry status, which improved with a modified test cut-off. Further studies are needed to confirm the cut-off accuracy.

An elevated rate of whole-genome duplications in cancers from Black patients

In the United States, Black individuals have higher rates of cancer mortality than any other racial group. Here, we examine chromosome copy number changes in cancers from more than 1800 self-reported Black patients. We find that tumors from self-reported Black patients are significantly more likely to exhibit whole-genome duplications (WGDs), a genomic event that enhances metastasis and aggressive disease, compared to tumors from self-reported white patients. This increase in WGD frequency is observed across multiple cancer types, including breast, endometrial, and lung cancer, and is associated with shorter patient survival. We further demonstrate that combustion byproducts are capable of inducing WGDs in cell culture, and cancers from self-reported Black patients exhibit mutational signatures consistent with exposure to these carcinogens. In total, these findings identify a type of genomic alteration that is associated with environmental exposures and that may influence racial disparities in cancer outcomes.

Reproductive and germ-cell mutagenic effects of poly-and perfluoroalkyl substances (PFAS) to Caenorhabditis elegans after multigenerational exposure

Per- and polyfluoroalkyl substances (PFAS) are a class of globally ubiquitous persistent organic pollutants (POPs). The developmental and reproductive toxicity of PFAS have attracted considerable attention. However, the influence of PFAS exposure on genomic stability of germ cells remains unexplored. In this study, we evaluated long-term reproductive toxicity of environmentally relevant levels of four long-chain PFAS compounds: perfluorooctanoic acid (PFOA, C8), perfluorononanoic acid (PFNA, C9), perfluorodecanoic acid (PFDA, C10), and perfluorooctanesulfonic acid (PFOS, C8), and examined their germ-cell mutagenicity in Caenorhabditis elegans. Our findings reveal that multigenerational exposure to PFAS exhibited minor impacts on development and reproduction of worms. Among all tested PFAS, PFNA significantly increased mutation frequencies of progeny by preferentially inducing T:A → C:G substitutions and small indels within repetitive regions. Further analysis of mutation spectra uncovered elevated frequencies of microhomology-mediated deletions and large deletions in PFOA-treated worms, indicating its potential activity in eliciting DNA double-strand breaks. This study provides the first comparative analysis of the genome-wide mutational profile of PFAS compounds, underscoring the importance of assessing germ-cell mutagenic actions of long-chain PFAS.

High-Grade Endometrial Cancer: Molecular Subtypes, Current Challenges, and Treatment Options

Although many recent advancements have been made in women's health, perhaps one of the most neglected areas of research is the diagnosis and treatment of high-grade endometrial cancer (EnCa). The molecular classification of EnCa in concert with histology was a major step forward. The integration of profiling for mismatch repair deficiency and Human Epidermal Growth Factor 2 (HER2) overexpression, can further inform treatment options, especially for drug resistant recurrent disease. Recent early phase trials suggest that regardless of subtype, combination therapy with agents that have distinct mechanisms of action is a fruitful approach to the treatment of high-grade EnCa. Unfortunately, although the importance of diagnosis and treatment of high-grade EnCa is well recognized, it is understudied compared to other gynecologic and breast cancers. There remains a tremendous need to couple molecular profiling and biomarker development with promising treatment options to inform new treatment strategies with higher efficacy and safety for all who suffer from high-grade recurrent EnCa.

A pilot study on the detection of microsatellite instability using long mononucleotide repeats in solid tumors

Microsatellite instability (MSI) status is a prognostic biomarker for immunotherapy in certain types of cancers, such as colorectal cancers (CRCs) and endometrial cancers (ECs). Tumors that are categorized as having high MSI (MSI-H) express high levels of neoantigens for immune recognition. The typical MSI test measures the length of short mononucleotide repeats (SMR) poly(A) 21-27; however, a limitation of this test is the difficulty in determining the shift size, particularly in endometrial cancer. To investigate an MSI detection assay with improved performance, the present study analyzed the use of poly(A) 40-44 mononucleotide repeats to detect the MSI status of 100 patients with either CRC (n=50) or EC (n=50). Capillary electrophoresis was used to evaluate five long mononucleotide repeat (LMR) markers, including poly(A) 40-A, 40-B, 40-C, 40-D and 44. The concordance rate of the LMR-MSI assay compared with an immunohistochemistry MSI detection assay was 96.0 and 95.1% for CRCs and ECs respectively, with the detection limit of the LMR-MSI assay demonstrated to be 2.5% MSI-H in HCT116 colorectal carcinoma cell lines. The LMR-MSI assay yielded a 95.1% concordance rate in ECs compared with that in the SMR-MSI test (87.8%). The LMR-MSI test identified a significantly higher mean shift size (13 bp) in MSI-H tumors compared with the SMR-MSI test (10 bp), in both EC and CRC tissue samples. Together, the present study suggested that the LMR-MSI test could potentially be a sensitive and practical technology for molecular laboratory testing, particularly in the use of immunotherapy for patients with CRCs and ECs.

Prevalence of KRAS amplification in patients with metastatic cancer: Real-world next-generation sequencing analysis

BACKGROUND

The Kirsten rat sarcoma virus (KRAS) is a prominent proto-oncogene. Several treatments for KRAS mutations have been developed. However, KRAS amplification, a KRAS alteration, is poorly understood, and there is currently no appropriate treatment other than conventional chemotherapy. This study aimed to elucidate the role of KRAS amplification in different types of cancers.

METHODS

From October 2019 to June 2023, we performed next-generation sequencing using Trusight Oncology 500 on 3895 patients with 37 different cancer types at the Samsung Medical Center. We analyzed the distribution of KRAS amplification according to cancer type and its correlation with tumor mutation burden (TMB). Concomitant KRAS mutations were also identified.

RESULTS

Of the total 3895 patients, 99 (2.5 %) had KRAS amplification. The highest frequency of KRAS amplification was detected in 2 % (27/1350) of patients with colorectal cancer, followed by 3.48 % (32/920) of patients with gastric cancer and 3.88 % (9/232) patients with of pancreatic cancer. MSI-High was not detected in patients with KRAS amplification. There was no correlation between KRAS copy number variation and TMB status. Among patients with KRAS amplification, 27.3 % (27/99) had a concomitant KRAS mutation. More than 50 % of patients had G12D or G12V mutations. In gastric cancer, patients with both KRAS amplification and mutation were extremely rare at 3.1 % (1/32); however, in colorectal cancer, more than half of the patients had KRAS amplification and mutation (51.9 %, 14/27). KRAS amplification and mutations are associated with mutations in tumor suppressor genes TP53, BRCA2, ARID1B, and PTCH1.

CONCLUSIONS

Of the 3895 patients with metastatic solid tumors, 99 (2.5 %) had KRAS amplification, and next-generation sequencing analysis provided a deeper understanding of KRAS amplification.

Comprehensive pan-cancer analysis reveals EPHB2 is a novel predictive biomarker for prognosis and immunotherapy response

PURPOSE

Recent studies have increasingly linked Ephrin receptor B2 (EPHB2) to cancer progression. However, comprehensive investigations into the immunological roles and prognostic significance of EPHB2 across various cancers remain lacking.

METHODS

We employed various databases and bioinformatics tools to investigate the impact of EPHB2 on prognosis, immune infiltration, genome instability, and response to immunotherapy. Validation of the correlation between EPHB2 expression and M2 macrophages included analyses using bulk and single-cell transcriptomic datasets, spatial transcriptomics, and multi-fluorescence staining. Moreover, we performed cMap web tool to screen for EPHB2-targeted compounds and assessed their potential through molecular docking and dynamics simulations. Additionally, in vitro validation using lung adenocarcinoma (LUAD) cell lines was conducted to confirm the bioinformatics predictions about EPHB2.

RESULTS

EPHB2 dysregulation was observed across multiple cancer types, where it demonstrated significant diagnostic and prognostic value. Gene Set Enrichment Analysis (GSEA) indicated that EPHB2 is involved in enhancing cellular proliferation, invasiveness of cancer cells, and modulation of the anti-cancer immune response. Furthermore, it is emerged as a pan-cancer marker for M2 macrophage infiltration, supported by integrated analyses of transcriptomics and multiple fluorescence staining. In LUAD cells, knockdown of EPHB2 expression led to a decrease in both cell proliferation and migratory activity.

CONCLUSION

EPHB2 expression may serve as a pivotal indicator of M2 macrophage infiltration, offering vital insights into tumor dynamics and progression across various cancers, including lung adenocarcinoma, highlighting its significant prognostic and therapeutic potential for further exploration.

Non-invasive CT radiomic biomarkers predict microsatellite stability status in colorectal cancer: a multicenter validation study

BACKGROUND

Microsatellite instability (MSI) status is a strong predictor of response to immunotherapy of colorectal cancer. Radiogenomic approaches promise the ability to gain insight into the underlying tumor biology using non-invasive routine clinical images. This study investigates the association between tumor morphology and the status of MSI versus microsatellite stability (MSS), validating a novel radiomic signature on an external multicenter cohort.

METHODS

Preoperative computed tomography scans with matched MSI status were retrospectively collected for 243 colorectal cancer patients from three hospitals: Seoul National University Hospital (SNUH); Netherlands Cancer Institute (NKI); and Fondazione IRCCS Istituto Nazionale dei Tumori, Milan Italy (INT). Radiologists delineated primary tumors in each scan, from which radiomic features were extracted. Machine learning models trained on SNUH data to identify MSI tumors underwent external validation using NKI and INT images. Performances were compared in terms of area under the receiving operating curve (AUROC).

RESULTS

We identified a radiomic signature comprising seven radiomic features that were predictive of tumors with MSS or MSI (AUROC 0.69, 95% confidence interval [CI] 0.54-0.84, p = 0.018). Integrating radiomic and clinical data into an algorithm improved predictive performance to an AUROC of 0.78 (95% CI 0.60-0.91, p = 0.002) and enhanced the reliability of the predictions.

CONCLUSION

Differences in the radiomic morphological phenotype between tumors MSS or MSI could be detected using radiogenomic approaches. Future research involving large-scale multicenter prospective studies that combine various diagnostic data is necessary to refine and validate more robust, potentially tumor-agnostic MSI radiogenomic models.

RELEVANCE STATEMENT

Noninvasive radiomic signatures derived from computed tomography scans can predict MSI in colorectal cancer, potentially augmenting traditional biopsy-based methods and enhancing personalized treatment strategies.

KEY POINTS

Noninvasive CT-based radiomics predicted MSI in colorectal cancer, enhancing stratification. A seven-feature radiomic signature differentiated tumors with MSI from those with MSS in multicenter cohorts. Integrating radiomic and clinical data improved the algorithm's predictive performance.

A comprehensive pan-cancer analysis revealing the role of ITPRIPL1 as a prognostic and immunological biomarker

Inositol 1,4,5-Trisphosphate Receptor-Interacting Protein-Like 1 (ITPRIPL1), a single-pass type I membrane protein located in the membrane, functions as an inhibitory ligand of CD3ε. Recent studies have shown that its expression suppresses T cells activation and promote tumor immune evasion. Despite increasing evidence suggesting that ITPRIPL1 plays a significant role in tumor growth, no systematic pan-cancer analysis of ITPRIPL1 has been conducted to date. This study utilized datasets curated from The Cancer Genome Atlas, Genotype Tissue-Expression, and Human Protein Atlas to investigate the relationship between ITPRIPL1 expression and clinical outcomes, immune infiltration, and drug sensitivity across 33 cancer types. We employed multiple methods to assess its prognostic value in pan-cancer, such as univariate Cox regression, survival analysis, and ROC curve analysis and explored the relationship between ITPRIPL1 and tumor mutation burden (TMB), tumor microsatellite instability (MSI), CNV, DNA methylation, immune-related genes, immune cell infiltration, and drug sensitivity to reveal its immunological role. The mRNA expression levels of the ITPRIPL1 gene vary significantly across multiple types of cancer and significantly reduced in breast cancer. Conversely, high ITPRIPL1 expression was associated with a better prognosis in BRCA. Furthermore, the expression of ITPRIPL1 highly correlates with the presence of tumor-infiltrating immune cells and immune checkpoint genes across various types of cancers. Additionally, ITPRIPL1 expression was associated with TMB in 6 cancer types and with MSI in 13 cancer types. High expression of ITPRIPL1 serves as a protective factor in certain cancer types, correlating with longer overall survival in BRCA. Our study further confirms that ITPRIPL1 participates in regulating immune infiltration and affecting the prognosis of patients in pan-cancer. These findings underscore the promising potential of ITPRIPL1 as a therapeutic target for human cancer.

Rediscovering immunohistochemistry in lung cancer

Several observations indicate that protein expression analysis by immunohistochemistry (IHC) remains relevant in individuals with non-small-cell lung cancer (NSCLC) when considering targeted therapy, as an early step in diagnosis and for therapy selection. Since the advent of next-generation sequencing (NGS), the role of IHC in testing for NSCLC biomarkers has been forgotten or ignored. We discuss how protein-level investigations maintain a critical role in defining sensitivity to lung cancer therapies in oncogene- and non-oncogene-addicted cases and in patients eligible for immunotherapy, suggesting that IHC testing should be reconsidered in clinical practice. We also argue how a panel of IHC tests should be considered complementary to NGS and other genomic assays. This is relevant to current clinical diagnostic practice but with potential future roles to optimize the selection of patients for innovative therapies. At the same time, strict validation of antibodies, assays, scoring systems, and intra- and interobserver reproducibility is needed.

Immune Checkpoint Inhibitors for Pediatric Cancers: Is It Still a Stalemate?

The knowledge surrounding the application of immune checkpoint inhibitors (ICIs) in the treatment of pediatric cancers is continuously expanding and evolving. These therapies work by enhancing the body's natural immune response against tumors, which may have been suppressed by certain pathways. The effectiveness of ICIs in treating adult cancers has been widely acknowledged. However, the results of early phase I/II clinical trials that exclusively targeted the use of ICIs for treating different pediatric cancers have been underwhelming. The response rates to ICIs have generally been modest, except for cases of pediatric classic Hodgkin lymphoma. There seems to be a notable disparity in the immunogenicity of childhood cancers compared to adult cancers, potentially accounting for this phenomenon. On average, childhood cancers tend to have significantly fewer neoantigens. In recent times, there has been a renewed sense of optimism regarding the potential benefits of ICI therapies for specific groups of children with cancer. In initial research, individuals diagnosed with pediatric hypermutated and SMARCB1-deficient cancers have shown remarkable positive outcomes when treated with ICI therapies. This is likely due to the underlying biological factors that promote the expression of neoantigens and inflammation within the tumor. Ongoing trials are diligently assessing the effectiveness of ICIs for pediatric cancer patients in these specific subsets. This review aimed to analyze the safety and effectiveness of ICIs in pediatric patients with different types of highly advanced malignancies.

Biomarker development for PD-(L)1 axis inhibition: a consensus view from the SITC Biomarkers Committee

Therapies targeting the programmed cell death protein-1/programmed death-ligand 1 (PD-L1) (abbreviated as PD-(L)1) axis are a significant advancement in the treatment of many tumor types. However, many patients receiving these agents fail to respond or have an initial response followed by cancer progression. For these patients, while subsequent immunotherapies that either target a different axis of immune biology or non-immune combination therapies are reasonable treatment options, the lack of predictive biomarkers to follow-on agents is impeding progress in the field. This review summarizes the current knowledge of mechanisms driving resistance to PD-(L)1 therapies, the state of biomarker development along this axis, and inherent challenges in future biomarker development for these immunotherapies. Innovation in the development and application of novel biomarkers and patient selection strategies for PD-(L)1 agents is required to accelerate the delivery of effective treatments to the patients most likely to respond.

Case report: Immunotherapy guided by molecular profiling of tumors: illustrative cases and literature review

Predictive biomarkers are necessary for the identification of immunotherapy-responsive patients. Tumor mutation burden (TMB), as determined by next-generation sequencing (NGS), and PD-L1 expression, as evaluated by Immunohistochemistry (IHC), are the biomarkers most frequently employed in clinical practice. In addition, microsatellite instability (MSI) was the first biomarker to demonstrate immunotherapy efficacy irrespective of the type of tumor and possesses a high predictive value. However, its limited use across most tumor types limits its therapeutic potential. This report describes two cancer patients with positive TMB and PD-L1 expression. The molecular profile of the tumor indicated that the first patient was responsive to Immune checkpoint inhibitors (ICI), while the second patient was resistant. These case studies demonstrate that tumor molecular analysis in combination with immunotherapy predictive biomarkers, such as PD-L1 expression and TMB, can enhance the prediction of response to ICI for specific patients. This methodology enables an individualized and improved approach to the treatment and management of the disease.

A Subset of Microsatellite Unstable Cancer Genomes Prone to Short Insertions over Deletions Is Associated with Elevated Anticancer Immunity

Deficiencies in DNA mismatch repair (MMRd) leave characteristic footprints of microsatellite instability (MSI) in cancer genomes. We used data from the Cancer Genome Atlas and International Cancer Genome Consortium to conduct a comprehensive analysis of MSI-associated cancers, focusing on indel mutational signatures. We classified MSI-high genomes into two subtypes based on their indel profiles: deletion-dominant (MMRd-del) and insertion-dominant (MMRd-ins). Compared with MMRd-del genomes, MMRd-ins genomes exhibit distinct mutational and transcriptomic features, including a higher prevalence of T>C substitutions and related mutation signatures. Short insertions and deletions in MMRd-ins and MMRd-del genomes target different sets of genes, resulting in distinct indel profiles between the two subtypes. In addition, indels in the MMRd-ins genomes are enriched with subclonal alterations that provide clues about a distinct evolutionary relationship between the MMRd-ins and MMRd-del genomes. Notably, the transcriptome analysis indicated that MMRd-ins cancers upregulate immune-related genes, show a high level of immune cell infiltration, and display an elevated neoantigen burden. The genomic and transcriptomic distinctions between the two types of MMRd genomes highlight the heterogeneity of genetic mechanisms and resulting genomic footprints and transcriptomic changes in cancers, which has potential clinical implications.

PD-L1 expression and microsatellite instability (MSI) in cancer of unknown primary site

BACKGROUND

Cancer of unknown primary site (CUP) is a heterogeneous group of tumors for which the origin remains unknown. Clinical outcomes might be influenced by regulatory processes in its microenvironment. Microsatellite instability (MSI) is a predictive biomarker for cancer immunotherapy and its status, as well as co-occurrence with PD-L1 expression, is poorly evaluated. We aim to evaluate the expression of PD-L1 and the status of MSI in CUP and their possible associations with clinical-pathological features.

METHODS

The combined positive score (CPS) PD-L1 expression was evaluated by immunohistochemistry. MSI status was assessed using a hexa-plex marker panel by polymerase chain reaction followed by fragment analysis.

RESULTS

Among the 166 cases, MSI analysis was conclusive in 120, with two cases being MSI positive (1.6%). PD-L1 expression was positive in 18.3% of 109 feasible cases. PD-L1 expression was significantly associated with non-visceral metastasis and a dominance of nodal metastasis. The median overall survival (mOS) was 3.7 (95% CI 1.6-5.8) months and patients who expressed PD-L1 achieved a better mOS compared to those who did not express PD-L1 (18.7 versus 3.0 months, p-value: < .001). ECOG-PS equal to or more than two and PD-L1 expression were independent prognostic factors in multivariate analysis (2.37 and 0.42, respectively).

CONCLUSION

PD-L1 is expressed in a subset (1/5) of patients with CUP and associated with improved overall survival, while MSI is a rare event. There is a need to explore better the tumor microenvironment as well as the role of immunotherapy to change such a bad clinical outcome.

Microsatellite Instability, Mismatch Repair, and Tumor Mutation Burden in Lung Cancer

Since US Food and Drug Administration approval of programmed death ligand 1 (PD-L1) as the first companion diagnostic for immune checkpoint inhibitors (ICIs) in non-small cell lung cancer, many patients have experienced increased overall survival. To improve selection of ICI responders versus nonresponders, microsatellite instability/mismatch repair deficiency (MSI/MMR) and tumor mutation burden (TMB) came into play. Clinical data show PD-L1, MSI/MMR, and TMB are independent predictive immunotherapy biomarkers. Harmonization of testing methodologies, optimization of assay design, and results analysis are ongoing. Future algorithms to determine immunotherapy eligibility might involve complementary use of current and novel biomarkers. Artificial intelligence could facilitate algorithm implementation to convert complex genetic data into recommendations for specific ICIs.

Targeting PI3K/AKT/mTOR signaling to overcome drug resistance in cancer

This review comprehensively explores the challenge of drug resistance in cancer by focusing on the pivotal PI3K/AKT/mTOR pathway, elucidating its role in oncogenesis and resistance mechanisms across various cancer types. It meticulously examines the diverse mechanisms underlying resistance, including genetic mutations, feedback loops, and microenvironmental factors, while also discussing the associated resistance patterns. Evaluating current therapeutic strategies targeting this pathway, the article highlights the hurdles encountered in drug development and clinical trials. Innovative approaches to overcome resistance, such as combination therapies and precision medicine, are critically analyzed, alongside discussions on emerging therapies like immunotherapy and molecularly targeted agents. Overall, this comprehensive review not only sheds light on the complexities of resistance in cancer but also provides a roadmap for advancing cancer treatment.

A cloud-based precision oncology framework for whole genome sequence analysis

Cancer is one of the wide-ranging diseases which have a high mortality rate impacting globally. This scenario can be switched by early detection and correct precision treatment, a major concern for cancer patients. Clinicians can figure out the best-suited treatments for cancer patients by analyzing the patient's genome, which will treat the patient well and minimize the chances of side effects as well. Therefore, we have developed a fast, robust, and efficient solution as our precision oncology framework based on the whole genome sequencing of the individual's DNA. This platform can perform the entire genomic analysis, starting from the quality assessment of the input file to the variant annotation and functional prediction, followed by a certain level of interpretation. This analysis helps in the molecular profiling of the tumors for the identification of the targetable alterations. It takes in FASTQ or BAM file as an input and provides us with two output reports: a primary report, which consists of the patients' details, a summary of the analysis, and a secondary report, which is an elaborated report comprised of numerous results obtained from the analysis such as base changes, codon changes, amino acid changes, TMB analysis, MSI analysis, the variant frequency with its effects and impacts, affected biomarkers, etc. This framework can be effectively utilized for cancer treatment guidance, identification and validation of novel biomarkers, oncology research & development, genomic analysis, and gene manipulation.

Death associated protein kinase 1 predicts the prognosis and the immunotherapy response of various cancers

BACKGROUND

Death Associated Protein Kinase 1 (DAPK1) is a calcium/calmodulin-dependent serine/threonine kinase, which has been reported to be a tumor suppressor with unbalanced expression in various tissues. However, its function in tumor immunotherapy is still unclear.

METHODS

The online GEPIA2 database was used to support TCGA results. We explored the DAPK1 pan-cancer genomic alteration analysis using the cBioPortal web tool. The Human Protein Atlas (HPA) was employed to mine DAPK1 protein information. We verified the expression of DAPK1 in lung adenocarcinoma samples using RT-qPCR. Subsequently, the relationship between the expression of DAPK1 and the clinical stage was analyzed. We used TIMER2.0 as the primary platform for studying DAPK1-related immune cell infiltration. Associations between DAPK1 and immunotherapy biomarkers were analyzed using Spearman correlation analysis. TMB and MSI expression was also examined. Finally, we used Kaplan-Meier Plots to evaluate the relationship between DAPK1 expression and the efficacy of immunotherapy.

RESULTS

DAPK1 is aberrantly expressed in most cancer types and has prognostic power in various cancers. Gene mutation was the most common DAPK1 alteration across pan-cancers. The DAPK1 protein was mainly localized to tumor cell centrosomes. DAPK1 was also significantly associated with immune-activated hallmarks, immune cell infiltration, and the expression of immunomodulators. Notably, DAPK1 can also significantly predict responses to anti-PD1 and anti-CTLA-4 therapy in cancer patients.

CONCLUSIONS

Our findings suggest that DAPK1 may not only be an effective prognostic factor in cancer patients but may also function as a promising predictive immunotherapy biomarker for cancer patients treated with immune checkpoint inhibitors.

Resistance to immune checkpoint inhibitors in colorectal cancer with deficient mismatch repair/microsatellite instability: misdiagnosis, pseudoprogression and/or tumor heterogeneity?

Colorectal carcinoma (CRC) with deficiency of the deficient mismatch repair (dMMR) pathway/microsatellite instability (MSI) is characterized by a high mutation load and infiltration of immune cells in the tumor microenvironment. In agreement with these findings, clinical trials have demonstrated a significant activity of immune checkpoint inhibitors (ICIs) in dMMR/MSI metastatic CRC (mCRC) patients and, more recently, in CRC patients with early disease undergoing neoadjuvant therapy. However, despite high response rates and durable clinical benefits, a fraction of mCRC patients, up to 30%, showed progressive disease when treated with single agent anti-programmed cell death 1 (PD-1) antibody. This article discusses the three main causes that have been associated with early progression of dMMR/MSI mCRC patients while on treatment with ICIs, i.e., misdiagnosis, pseudoprogression and tumor heterogeneity. While pseudoprogression probably does not play a relevant role, data from clinical studies demonstrate that some dMMR/MSI CRC cases with rapid progression on ICIs may be misdiagnosed, underlining the importance of correct diagnostics. More importantly, evidence suggests that dMMR/MSI mCRC is a heterogeneous group of tumors with different sensitivity to ICIs. Therefore, we propose novel diagnostic and therapeutic strategies to improve the outcome of dMMR/MSI CRC patients.

Immunotherapy in the neoadjuvant treatment of gastrointestinal tumors: is the time ripe?

Immune checkpoint inhibitors (ICIs) revolutionized the management of mismatch repair-deficient (dMMR)/microsatellite instability-high (MSI-H) gastrointestinal (GI) cancers. Based on notable results observed in the metastatic setting, several clinical trials investigated ICIs as neoadjuvant treatment (NAT) for localized dMMR/MSI-H GI cancers, achieving striking results in terms of clinical and pathological responses and creating the opportunity to spare patients from neoadjuvant chemotherapy and/or radiotherapy and even surgical resection. Nevertheless, these impressive findings are mainly derived from small proof of concept phase II studies and there are still several open questions to address. Moreover, dMMR/MSI-H represents a limited subgroup accounting for less than 10% of GI cancers. Consequently, many efforts have been produced to investigate neoadjuvant ICIs also in mismatch repair-proficient/microsatellite stable (MSS) cancers, considering the potential synergistic effect in combining immune-targeted agents with standard therapies such as chemo and/or radiotherapy. However, results for combining ICIs to the standard of care in the unselected population are still unsatisfactory, without improvements in event-free survival in esophago-gastric adenocarcinoma for the addition of pembrolizumab to chemotherapy, and sometimes limited benefit in patients with locally advanced rectal cancer. Therefore, a major challenge will be to identify among the heterogenous spectrum of this disease, those patients that could take advantage of neoadjuvant immunotherapy and deliver the most effective treatment. In this review we discuss the rationale of NAT in GI malignancies, summarize the available evidence regarding the completed trials that evaluated this treatment strategy in both MSI-H and MSS tumors. Finally, we discuss ongoing studies and future perspectives to render neoadjuvant immunotherapy another arrow in the quiver for the treatment of locally advanced GI tumors.

Early-Onset Colorectal Cancer-A Retrospective Study from a Tertiary Referral Hospital in Romania

Early-onset colorectal cancer emerges as a distinctive clinical and biological entity and is generally defined as the onset of colon or rectal neoplasia before the age of 50. Several reports describe an increasing incidence worldwide of colorectal cancers occurring in individuals younger than 50 years, along with particular histologic and molecular features. Although heredity may be an explanation in some cases with young-onset colorectal cancer, other driving factors remain partially unknown. The present study explores demographic, clinical, and pathological features within a group of patients diagnosed with colorectal cancer before the age of 50. It is a retrospective survey based on data collected between 2017 and 2023 within three surgical departments from a tertiary Romanian hospital. The clinical and pathological features we identified (later-stage disease, distal colon tumor localization, mucinous histology) are mainly superimposed with the existing data in the literature regarding this pathology. In order to lower the burden that colorectal neoplasia diagnosed in the young implies, a change of paradigm should be made in terms of establishing effective and targeted screening programs but also in the direction of enhancing complex clinical, pathological, and molecular diagnosis.

Establishment of a novel efferocytosis potential index predicts prognosis and immunotherapy response in cancers

The biological function and prognostic value of efferocytosis in cancer remains unclear. In this study, we systematically analysed the expression profiles and genetic variations of 50 efferocytosis-related regulator genes in 33 cancer types. Using data from The Cancer Genome Atlas, we established an efferocytosis potential index (EPI) model to represent the efferocytosis level in each cancer type. The relationship between the EPI and prognosis, immune-related molecules, specific pathways, and drug sensitivity was determined. We found that efferocytosis regulator genes were abnormally expressed in cancer tissue, perhaps owing to copy number variations, gene alterations, and DNA methylation. For the most part, the EPI was higher in tumour vs. normal tissues. In most of the 33 cancer types, it positively correlated with cell death- and immune-related pathway enrichment, the tumour microenvironment, immune infiltration, and drug sensitivity. For specific cancers, a high EPI may be a prognostic risk factor and, in patients treated receiving immune checkpoint therapy, a predictor of poor prognosis. Our study reveals the biological functions of efferocytosis-related regulator genes in distinct cancers and highlights the potential of efferocytosis intervention in cancer therapy.

Feature Engineering-Assisted Drug Repurposing on Disease-Drug Transcriptome Profiles in Gastric Cancer

Gastric cancer is one of the most common and deadly types of cancer in the world. To develop new biomarkers and drugs to diagnose and treat this cancer, it is necessary to identify the differences between the transcriptome profiles of gastric cancer and healthy individuals, identify critical genes associated with these differences, and make potential drug predictions based on these genes. In this study, using two gene expression datasets related to gastric cancer (GSE19826 and GSE79973), 200 genes that were ready for machine learning were selected, and their expression levels were analyzed. The best 100 genes for the model were chosen with the permutation feature importance method, and central genes, such as SCARB1, ETV3, SPATA17, FAM167A-AS1, and MTBP, which were shown to be associated with gastric cancer, were identified. Then, using the drug repurposing method with the Connectivity Map CLUE Query tools, potential drugs such as Forskolin, Gestrinone, Cediranib, Apicidine, and Everolimus, which showed a highly negative correlation with the expression levels of the selected genes, were identified. This study provides a method to develop new approaches to diagnosing and treating gastric cancer by comparing the transcriptome profiles of patients gastric cancer and performing a feature engineering-assisted drug repurposing analysis based on cancer data.

Unveiling the Influence of AI Predictive Analytics on Patient Outcomes: A Comprehensive Narrative Review

This comprehensive literature review explores the transformative impact of artificial intelligence (AI) predictive analytics on healthcare, particularly in improving patient outcomes regarding disease progression, treatment response, and recovery rates. AI, encompassing capabilities such as learning, problem-solving, and decision-making, is leveraged to predict disease progression, optimize treatment plans, and enhance recovery rates through the analysis of vast datasets, including electronic health records (EHRs), imaging, and genetic data. The utilization of machine learning (ML) and deep learning (DL) techniques in predictive analytics enables personalized medicine by facilitating the early detection of conditions, precision in drug discovery, and the tailoring of treatment to individual patient profiles. Ethical considerations, including data privacy, bias, and accountability, emerge as vital in the responsible implementation of AI in healthcare. The findings underscore the potential of AI predictive analytics in revolutionizing clinical decision-making and healthcare delivery, emphasizing the necessity of ethical guidelines and continuous model validation to ensure its safe and effective use in augmenting human judgment in medical practice.

Artificial Intelligence in Oncology: Current Landscape, Challenges, and Future Directions

Artificial intelligence (AI) in oncology is advancing beyond algorithm development to integration into clinical practice. This review describes the current state of the field, with a specific focus on clinical integration. AI applications are structured according to cancer type and clinical domain, focusing on the four most common cancers and tasks of detection, diagnosis, and treatment. These applications encompass various data modalities, including imaging, genomics, and medical records. We conclude with a summary of existing challenges, evolving solutions, and potential future directions for the field.

SIGNIFICANCE

AI is increasingly being applied to all aspects of oncology, where several applications are maturing beyond research and development to direct clinical integration. This review summarizes the current state of the field through the lens of clinical translation along the clinical care continuum. Emerging areas are also highlighted, along with common challenges, evolving solutions, and potential future directions for the field.

High-Throughput Antigen Microarray Identifies Longitudinal Prognostic Autoantibody for Chemoimmunotherapy in Advanced Non-Small Cell Lung Cancer

Chemoimmunotherapy has evolved as a standard treatment for advanced non-small cell lung cancer (aNSCLC). However, inevitable drug resistance has limited its efficacy, highlighting the urgent need for biomarkers of chemoimmunotherapy. A three-phase strategy to discover, verify, and validate longitudinal predictive autoantibodies (AAbs) for aNSCLC before and after chemoimmunotherapy was employed. A total of 528 plasma samples from 267 aNSCLC patients before and after anti-PD1 immunotherapy were collected, plus 30 independent formalin-fixed paraffin-embedded samples. Candidate AAbs were firstly selected using a HuProt high-density microarray containing 21,000 proteins in the discovery phase, followed by validation using an aNSCLC-focused microarray. Longitudinal predictive AAbs were chosen for ELISA based on responders versus non-responders comparison and progression-free survival (PFS) survival analysis. Prognostic markers were also validated using immunohistochemistry and publicly available immunotherapy datasets. We identified and validated a panel of two AAbs (MAX and DHX29) as pre-treatment biomarkers and another panel of two AAbs (MAX and TAPBP) as on-treatment predictive markers in aNSCLC patients undergoing chemoimmunotherapy. All three AAbs exhibited a positive correlation with early responses and PFS (p < 0.05). The kinetics of MAX AAb showed an increasing trend in responders (p < 0.05) and a tendency to initially increase and then decrease in non-responders (p < 0.05). Importantly, MAX protein and mRNA levels effectively discriminated PFS (p < 0.05) in aNSCLC patients treated with immunotherapy. Our results present a longitudinal analysis of changes in prognostic AAbs in aNSCLC patients undergoing chemoimmunotherapy.

Microsatellite instability and mismatch repair protein deficiency: equal predictive markers?

Current clinical guidelines recommend mismatch repair (MMR) protein immunohistochemistry (IHC) or molecular microsatellite instability (MSI) tests as predictive markers of immunotherapies. Most of the pathological guidelines consider MMR protein IHC as the gold standard test to identify cancers with MMR deficiency and recommend molecular MSI tests only in special circumstances or to screen for Lynch syndrome. However, there are data in the literature which suggest that the two test types may not be equal. For example, molecular epidemiology studies reported different rates of deficient MMR (dMMR) and MSI in various cancer types. Additionally, direct comparisons of the two tests revealed relatively frequent discrepancies between MMR IHC and MSI tests, especially in non-colorectal and non-endometrial cancers and in cases with unusual dMMR phenotypes. There are also scattered clinical data showing that the efficacy of immune checkpoint inhibitors is different if the patient selection was based on dMMR versus MSI status of the cancers. All these observations question the current dogma that dMMR phenotype and genetic MSI status are equal predictive markers of the immunotherapies.

Molecular insights into clinical trials for immune checkpoint inhibitors in colorectal cancer: Unravelling challenges and future directions

Colorectal cancer (CRC) is a complex disease with diverse etiologies and clinical outcomes. Despite considerable progress in development of CRC therapeutics, challenges remain regarding the diagnosis and management of advanced stage metastatic CRC (mCRC). In particular, the five-year survival rate is very low since mCRC is currently rarely curable. Over the past decade, cancer treatment has significantly improved with the introduction of cancer immunotherapies, specifically immune checkpoint inhibitors. Therapies aimed at blocking immune checkpoints such as PD-1, PD-L1, and CTLA-4 target inhibitory pathways of the immune system, and thereby enhance anti-tumor immunity. These therapies thus have shown promising results in many clinical trials alone or in combination. The efficacy and safety of immunotherapy, either alone or in combination with CRC, have been investigated in several clinical trials. Clinical trials, including KEYNOTE-164 and CheckMate 142, have led to Food and Drug Administration approval of the PD-1 inhibitors pembrolizumab and nivolumab, respectively, for the treatment of patients with unresectable or metastatic microsatellite instability-high or deficient mismatch repair CRC. Unfortunately, these drugs benefit only a small percentage of patients, with the benefits of immunotherapy remaining elusive for the vast majority of CRC patients. To this end, primary and secondary resistance to immunotherapy remains a significant issue, and further research is necessary to optimize the use of immunotherapy in CRC and identify biomarkers to predict the response. This review provides a comprehensive overview of the clinical trials involving immune checkpoint inhibitors in CRC. The underlying rationale, challenges faced, and potential future steps to improve the prognosis and enhance the likelihood of successful trials in this field are discussed.

The intricate dance of tumor evolution: Exploring immune escape, tumor migration, drug resistance, and treatment strategies

Recent research has unveiled fascinating insights into the intricate mechanisms governing tumor evolution. These studies have illuminated how tumors adapt and proliferate by exploiting various factors, including immune evasion, resistance to therapeutic drugs, genetic mutations, and their ability to adapt to different environments. Furthermore, investigations into tumor heterogeneity and chromosomal aberrations have revealed the profound complexity that underlies the evolution of cancer. Emerging findings have also underscored the role of viral influences in the development and progression of cancer, introducing an additional layer of complexity to the field of oncology. Tumor evolution is a dynamic and complex process influenced by various factors, including immune evasion, drug resistance, tumor heterogeneity, and viral influences. Understanding these elements is indispensable for developing more effective treatments and advancing cancer therapies. A holistic approach to studying and addressing tumor evolution is crucial in the ongoing battle against cancer. The main goal of this comprehensive review is to explore the intricate relationship between tumor evolution and critical aspects of cancer biology. By delving into this complex interplay, we aim to provide a profound understanding of how tumors evolve, adapt, and respond to treatment strategies. This review underscores the pivotal importance of comprehending tumor evolution in shaping effective approaches to cancer treatment.

Mitochondria-related chemoradiotherapy resistance genes-based machine learning model associated with immune cell infiltration on the prognosis of esophageal cancer and its value in pan-cancer

Esophageal cancer, known for its high incidence and low five-year survival rate, poses significant treatment challenges. A key aspect of this challenge is the close link between mitochondria and resistance to chemoradiotherapy (CRT). Currently, there is a scarcity of biomarkers for predicting CRT response and prognosis in esophageal cancer. Our study addresses this gap by developing a prognostic model that incorporates mitochondria-related CRT resistance (MRCRTR) genes, including CTSL, TBL1X, CLN8, MMP1, PDPN, and MRPL37. Survival analysis using Kaplan-Meier curves reveals that patients with high MRCRTR scores have lower survival rates than those with low scores. Utilizing a nomogram, we successfully predict the one-, two-, and three-year overall survival rates for esophageal cancer patients. Cox regression analysis confirms the MRCRTR score as an independent prognostic factor. Furthermore, our single-cell and correlation analyses suggested that MRCRTR genes might influence CRT resistance by modulating the immune microenvironment and impacting angiogenesis. Our pan-cancer analysis also indicates the potential applicability of MRCRTR scores to head and neck squamous cell carcinoma. The validation of these findings, conducted with samples from Xiang-ya Hospital, aligns closely with our bioinformatics results. Our study not only explores the role of MRCRTR genes in predicting the prognosis of esophageal cancer but also enhances the understanding of the interplay between CRT, mitochondria, and patient outcomes.

Tissue-Agnostic Cancer Therapy Approvals

Tumor-agnostic, or histology-agnostic, cancer therapy marks a groundbreaking evolution in the realm of precision oncology. In stark contrast to conventional cancer treatments that categorize malignancies based on their tissue of origin (eg, breast, lung, renal cell, etc), tumor-agnostic therapies transcend histologic boundaries, honing in on the genetic and molecular attributes of tumors, regardless of their location. This article offers a comprehensive review of the current landscape of tissue-agnostic cancer therapies and provides clinical insights to empower surgical oncologists with a deeper understanding of these innovative therapeutic approaches.

Genomic Profiling and Molecular Characterisation of Metastatic Urothelial Carcinoma

The clinical management of metastatic urothelial carcinoma (mUC) is undergoing a major paradigm shift; the integration of immune checkpoint inhibitors (ICIs) and antibody-drug conjugates (ADCs) into the mUC therapeutic strategy has succeeded in improving platinum-based chemotherapy outcomes. Given the expanding therapeutic armamentarium, it is crucial to identify efficacy-predictive biomarkers that can guide an individual patient's therapeutic strategy. We reviewed the literature data on mUC genomic alterations of clinical interest, discussing their prognostic and predictive role. In particular, we explored the role of the fibroblast growth factor receptor (FGFR) family, epidermal growth factor receptor 2 (HER2), mechanistic target of rapamycin (mTOR) axis, DNA repair genes, and microsatellite instability. Currently, based on the available clinical data, FGFR inhibitors and HER2-directed ADCs are effective therapeutic options for later lines of biomarker-driven mUC. However, emerging genomic data highlight the opportunity for earlier use and/or combination with other drugs of both FGFR inhibitors and HER2-directed ADCs and also reveal additional potential drug targets that could change mUC management.

Potential role of immune cell therapy in gynecological cancer and future promises: a comprehensive review

Gynecological malignancies are most leading causes of death among women worldwide. The high prevalence of gynecologic malignancies remains significant, necessitating to turn the novel treatment approach like immunotherapy, wherein cancer cells are killed by the invasion of immune system. In recent year, immunotherapy has mostly an advanced treatment approach to repressing the tumor cells survival, proliferation, and invasion via the activation of immune systems. Moreover, various types of immune cells including T-cells, B-cells, and dendritic cells are associated with the immunotherapeutic strategy in cancer treatment. Although the significant role of T-cells against cancer is well established, while B-cells and dendritic cells also play an important role against different gynecological cancer by regulating the immune system. This review focuses on that arena and highlight the role of immune cells in the treatment of gynaecological cancer. Various immune cell-based anticancer therapies such as T-cell therapies, Adoptive Cellular transfer, B-cell therapies as well as approaches to Dendritic Cell therapies have been discussed in detail. Furthermore, the clinical settings and future avenues regarding immunotherapy on gynecological cancer have also been reviewed and illuminated in the recent study.

A new strategy for immunotherapy of microsatellite-stable (MSS)-type advanced colorectal cancer: Multi-pathway combination therapy with PD-1/PD-L1 inhibitors

Colorectal cancer (CRC) is a frequent gastrointestinal malignancy with high rates of morbidity and mortality; 85% of these tumours are proficient mismatch repair (pMMR)-microsatellite instability-low (MSI-L)/microsatellite stable (MSS) CRC known as 'cold' tumours that are resistant to immunosuppressive drugs. Monotherapy with programmed death 1 (PD-1)/programmed death ligand 1 (PD-L1) inhibitors is ineffective for treating MSS CRC, making immunotherapy for MSS CRC a bottleneck. Recent studies have found that the multi-pathway regimens combined with PD-1/PD-L1 inhibitors can enhance the efficacy of anti-PD-1/PD-L1 in MSS CRC by increasing the number of CD8+ T cells, upregulating PD-L1 expression and improving the tumour microenvironment. This paper reviews the research progress of PD-1/PD-L1 inhibitors in combination with cytotoxic T-lymphocyte-associated antigen 4 (CTLA-4) inhibitors, oncolytic virus, intestinal flora, antiangiogenic agents, chemotherapy, radiotherapy and epigenetic drugs for the treatment of pMMR-MSI-L/MSS CRC.

Genetically driven predisposition leads to an unusually genomic unstable renal cell carcinoma

Renal cell carcinoma originates from the lining of the proximal convoluted renal tubule and represents the most common type of kidney cancer. Risk factors and comorbidities might be associated to renal cell carcinoma, while a small fraction of 2-3% emerges from patients with predisposing cancer syndromes, typically associated to hereditary mutations in VHL, folliculin, fumarate hydratase or MET genes. Here, we report a case of renal cell carcinoma in patient with concurrent germline mutations in BRCA1 and RAD51 genes. This case displays an unusual high mutational burden and chromosomal aberrations compared to the typical profile of renal cell carcinoma. Mutational analysis on whole genome sequencing revealed an enrichment of the MMR2 mutational signature, which is indicative of impaired DNA repair capacity. Overall, the tumor displayed a profile of unusual high genomic instability which suggests a possible origin from germline predisposing mutations in the DNA repair genes BRCA1 and RAD51. While BRCA1 and RAD51 germline mutations are well-characterised in breast and ovarian cancer, their role in renal cell carcinoma is still largely unexplored. The genomic instability detected in this case of renal cell carcinoma, along with the presence of unusual mutations, might offer support to clinicians for the development of patient-tailored therapies.

Prognostic significance and immunological role of HPRT1 in human cancers

Hypoxanthine phosphoribosyl transferase 1 (HPRT1), once considered a housekeeping gene, has been identified as playing an important role in several tumors. Its role in pan-cancer, however, has not been systematically studied. This study evaluates the relationship between HPRT1 and clinical parameters, survival prognosis, and tumor immunity based on multi omics data from the Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases. Drug sensitivity analysis screened 16 effective drugs against HPRT1, exploring the interactions with chemicals and genes. The significance of HPRT1 in tumor immunotherapy has also been investigated. Immunohistochemistry confirmed significant differences in the expression of HPRT1 between five tumor types (colon adenocarcinoma [COAD], head-neck squamous cell carcinoma [HNSC], lung adenocarcinoma [LUAD], thyroid carcinoma [THCA], and uterine corpus endometrial carcinoma [UCEC]) and adjacent normal tissues (P < 0.05). HPRT1 competitive endogenous RNA network was constructed in HNSC. Through cytological experiments, it was verified that HPRT1 plays a carcinogenic role in HNSC and is associated with tumor cell proliferation, migration, invasion, and apoptosis. In addition, there was a significant positive correlation between HPRT1 and programmed cell death-1 (PD-1) expression in HNSC (P < 0.05). These findings suggest that HPRT1 may be a potential biomarker for predicting and treating cancer.

Biomarkers and computational models for predicting efficacy to tumor ICI immunotherapy

Numerous studies have shown that immune checkpoint inhibitor (ICI) immunotherapy has great potential as a cancer treatment, leading to significant clinical improvements in numerous cases. However, it benefits a minority of patients, underscoring the importance of discovering reliable biomarkers that can be used to screen for potential beneficiaries and ultimately reduce the risk of overtreatment. Our comprehensive review focuses on the latest advancements in predictive biomarkers for ICI therapy, particularly emphasizing those that enhance the efficacy of programmed cell death protein 1 (PD-1)/programmed cell death-ligand 1 (PD-L1) inhibitors and cytotoxic T-lymphocyte antigen-4 (CTLA-4) inhibitors immunotherapies. We explore biomarkers derived from various sources, including tumor cells, the tumor immune microenvironment (TIME), body fluids, gut microbes, and metabolites. Among them, tumor cells-derived biomarkers include tumor mutational burden (TMB) biomarker, tumor neoantigen burden (TNB) biomarker, microsatellite instability (MSI) biomarker, PD-L1 expression biomarker, mutated gene biomarkers in pathways, and epigenetic biomarkers. TIME-derived biomarkers include immune landscape of TIME biomarkers, inhibitory checkpoints biomarkers, and immune repertoire biomarkers. We also discuss various techniques used to detect and assess these biomarkers, detailing their respective datasets, strengths, weaknesses, and evaluative metrics. Furthermore, we present a comprehensive review of computer models for predicting the response to ICI therapy. The computer models include knowledge-based mechanistic models and data-based machine learning (ML) models. Among the knowledge-based mechanistic models are pharmacokinetic/pharmacodynamic (PK/PD) models, partial differential equation (PDE) models, signal networks-based models, quantitative systems pharmacology (QSP) models, and agent-based models (ABMs). ML models include linear regression models, logistic regression models, support vector machine (SVM)/random forest/extra trees/k-nearest neighbors (KNN) models, artificial neural network (ANN) and deep learning models. Additionally, there are hybrid models of systems biology and ML. We summarized the details of these models, outlining the datasets they utilize, their evaluation methods/metrics, and their respective strengths and limitations. By summarizing the major advances in the research on predictive biomarkers and computer models for the therapeutic effect and clinical utility of tumor ICI, we aim to assist researchers in choosing appropriate biomarkers or computer models for research exploration and help clinicians conduct precision medicine by selecting the best biomarkers.

Detecting Somatic Mutations Without Matched Normal Samples Using Long Reads

DNA sequencing of tumours to identify somatic mutations has become a critical tool to guide the type of treatment given to cancer patients. The gold standard for mutation calling is comparing sequencing data from the tumour to a matched normal sample to avoid mis-classifying inherited SNPs as mutations. This procedure works extremely well, but in certain situations only a tumour sample is available. While approaches have been developed to find mutations without a matched normal, they have limited accuracy or require specific types of input data (e.g. ultra-deep sequencing). Here we explore the application of single molecule long read sequencing to calling somatic mutations without matched normal samples. We develop a simple theoretical framework to show how haplotype phasing is an important source of information for determining whether a variant is a somatic mutation. We then use simulations to assess the range of experimental parameters (tumour purity, sequencing depth) where this approach is effective. These ideas are developed into a prototype somatic mutation caller, smrest, and its use is demonstrated on two highly mutated cancer cell lines. Finally, we argue that this approach has potential to measure clinically important biomarkers that are based on the genome-wide distribution of mutations: tumour mutation burden and mutation signatures.

A Novel DNA Variant in SMARCA4 Gene Found in a Patient Affected by Early Onset Colon Cancer

Colorectal cancer is the third leading cause of death from neoplasia worldwide. Thanks to new screening programs, we are now seeing an increase in Early Onset of ColoRectal Cancer (EOCRC) in patients below the age of 50. Herein, we report a clinical case of a woman affected by EOCRC. This case illustrates the importance of genetic predisposition testing also in tumor patients. Indeed, for our patient, we used a combined approach of multiple molecular and cellular biology technologies that revealed the presence of an interesting novel variant in the SMARCA4 gene. The latter gene is implicated in damage repair processes and related, if mutated, to the onset of various tumor types. In addition, we stabilized Patient-Derived Organoids from the tumor tissue of the same patient and the result confirmed the presence of this novel pathogenic variant that has never been found before even in early onset cancer. In conclusion, with this clinical case, we want to underscore the importance of including patients even those below the age of 50 years in appropriate screening programs which should also include genetic tests for predisposition to early onset cancers.

Location matters: spatial dynamics of tumor-infiltrating T cell subsets is prognostic in colon cancer

Background

Colon cancer is a heterogeneous disease and consists of various molecular subtypes. Despite advances in high-throughput expression profiling, limitations remain in predicting clinical outcome and assigning specific treatment to individual cases. Tumor-immune interactions play a critical role, with tumors that activate the immune system having better outcome for the patient. The localization of T cells within tumor epithelium, to enable direct contact, is essential for antitumor function, but bulk DNA/RNA sequencing data lacks spatial distribution information. In this study, we provide spatial T cell tumor distribution and connect these data with previously determined genomic data in the AC-ICAM colon cancer patient cohort.

Methods

Colon cancer patients (n=90) with transcriptome data available were selected. We used a custom multiplex immunofluorescence assay on colon tumor tissue sections for quantifying T cell subsets spatial distribution in the tumor microenvironment, in terms of cell number, location, mutual distance, and distance to tumor cells. Statistical analyses included the previously determined Immunologic Constant of Rejection (ICR) transcriptome correlation and patient survival, revealing potential prognostic value in T cell spatial distribution.

Results

T cell phenotypes were characterized and CD3+CD8-FoxP3- T cells were found to be the predominant tumor-infiltrating subtype while CD3+FoxP3+ T cells and CD3+CD8+ T cells showed similar densities. Spatial distribution analysis elucidated that proliferative T cells, characterized by Ki67 expression, and Granzyme B-expressing T cells were predominantly located within the tumor epithelium. We demonstrated an increase in immune cell density and a decrease in the distance of CD3+CD8+ T cells to the nearest tumor cell, in the immune active, ICR High, immune subtypes. Higher densities of stromal CD3+FoxP3+ T cells showed enhanced survival outcomes, and patients exhibited superior clinical benefits when greater spatial distances were observed between CD3+CD8-FoxP3- or CD3+CD8+ T cells and CD3+FoxP3+ T cells.

Conclusion

Our study's in-depth analysis of the spatial distribution and densities of major T cell subtypes within the tumor microenvironment has provided valuable information that paves the way for further research into the intricate relationships between immune cells and colon cancer development.

Molecular diagnostics tailoring personalized cancer therapy-an oncologist's view

Medical oncology is rapidly evolving with the implementation of personalized, targeted therapies. Advances in molecular diagnostics and the biologic understanding of cancer pathophysiology led to the identification of specific genetic alterations as drivers of cancer progression. Further, improvements in drug development enable the direct interference with these pathways, which allow tailoring personalized treatments based on a distinct molecular characterization of tumors. Thereby, we are currently experiencing a paradigm-shift in the treatment of cancers towards cancer-type agnostic, molecularly targeted, personalized therapies. However, this concept has several important hurdles and limitations to overcome to ultimately increase the proportion of patients benefitting from the precision oncology approach. These include the assessment of clinical relevancy of identified alterations, capturing and interpreting levels of heterogeneity based on intra-tumoral or time-dependent molecular evolution, and challenges in the practical implementation of precision oncology in routine clinical care. In the present review, we summarize the current state of cancer-agnostic precision oncology, discuss the concept of molecular tumor boards, and consider current limitations of personalized cancer therapy. Further, we provide an outlook towards potential future developments including the implementation of functionality assessments of identified genetic alterations and the broader use of liquid biopsies in order to obtain more comprehensive and longitudinal genetic information that might guide personalized cancer therapy in the future.

Latest advances in immuno-oncology for endometrial cancer: single-agent and combination regimens

PURPOSE OF REVIEW

The scope of immuno-oncology in endometrial cancer has changed rapidly in the last several years, requiring up-to-date knowledge for those who treat these patients.

RECENT FINDINGS

This article will focus on molecular profiling, recent trials, and FDA approvals of targeted immuno-oncology medications in endometrial cancer. These include immune checkpoint inhibitors alone or with combination treatment.

SUMMARY

The publication of the TCGA has led to significant focus on molecular subgroupings into POLEm, MMRd, NSMP, and p53m groups. For those patients with MMRd vs. MMRp tumors, there are indications for single agent immune checkpoint inhibitors with dostarlimab or pembrolizumab. For those with MMRp tumors, the addition of lenvatinib to pembrolizumab has proven clinical benefit. The recent publication of the RUBY and NRG-GY018 trials have shown clinical benefit in both subgroups with addition of immune checkpoint inhibitor to platinum-based chemotherapy. Now there is approval for use of dostarlimab in frontline chemotherapy and maintenance for advanced stage or recurrent endometrial cancer. Several upcoming trials investigating molecular subgroups from the TCGA are eagerly anticipated.

Existing and emerging biomarkers in hepatocellular carcinoma: relevance in staging, determination of minimal residual disease, and monitoring treatment response: a narrative review

Background and Objective

With the development of novel active systemic therapies, the landscape of hepatocellular carcinoma (HCC) management is rapidly changing. However, HCC lacks sensitive and specific biomarkers to predict prognosis, monitor for minimal residual disease after locoregional therapy, and predict treatment response. In this review, we aim to summarize the best supporting evidence for refining existing, and development of novel biomarkers for staging, prognosis, determination of minimal residual disease and monitoring treatment response in HCC, focusing on those with evidence in clinical trials.

Methods

PubMed and Embase databases were searched using the keywords; hepatocellular carcinoma, biomarker, minimal residual disease, surveillance, prognosis, staging, alpha-fetoprotein (AFP), liquid biopsy, treatment response, adjuvant, immunotherapy. Relevant clinical studies were included.

Key Content and Findings

AFP remains the major workhorse as the most widely used biomarker in HCC, however, its lack of wide applicability due to the high proportion of patients with HCC who are AFP negative, limits its value throughout all stages of HCC management. Significant work has been done to combine AFP with other clinical and serologic factors to increase its accuracy and utility as a biomarkers. However, it is likely that other more novel biomarkers such as those obtained through liquid biopsy will provide the prognostic power necessary for applications such as detecting recurrence and predicting treatment response. Liquid biopsy provides not only a wealth of potential biomarkers including circulating tumor cells and cell-free RNA/DNA, but also the ability to examine the mutational characteristics of the tumor with next generation sequencing. While early evidence supports the potential impact of many new biomarkers, validation in large clinical trials is lacking.

Conclusions

This review highlights the paucity of sensitive and specific, widely applicable biomarkers, throughout all phases of management of HCC and summarizes evidence on biomarkers currently in use, as well as those in development and validation. Inclusion of biomarker analysis through clinical trials in HCC is critical to development of optimal therapeutic regimens, and improve patient outcomes.

Case report: Efficacy of immunotherapy as conversion therapy in dMMR/MSI-H colorectal cancer: a case series and review of the literature

Immunotherapy has demonstrated a role in the therapeutic landscape of a small subset of patients with colorectal carcinoma (CRC) that harbor a microsatellite instability (MSI-H) status due to a deficient DNA mismatch repair (dMMR) system. The remarkable responses to immune checkpoint inhibitors (ICIs) are now being tested in the neoadjuvant setting in localized CRC, where the dMMR/MSI-H status can be found in up to 15% of patients, with remarkable results obtained in NICHE2 and 3 trials, among others. This case series aims to report our experience at a tertiary center and provide a comprehensive analysis of the possible questions and challenges to overcome if ICIs were established as standard of care in a neoadjuvant setting, as well as the potential role they may have as conversion therapy not only in locoregional advanced CRC but also in oligometastatic disease.

Wakefield M. The role of aberrant DNA methylation in cancer initiation and clinical impacts

Epigenetic alterations, including aberrant DNA methylation, are now recognized as bone fide hallmarks of cancer, which can contribute to cancer initiation, progression, therapy responses and therapy resistance. Methylation of gene promoters can have a range of impacts on cancer risk, clinical stratification and therapeutic outcomes. We provide several important examples of genes, which can be silenced or activated by promoter methylation and highlight their clinical implications. These include the mismatch DNA repair genes MLH1 and MSH2, homologous recombination DNA repair genes BRCA1 and RAD51C, the TERT oncogene and genes within the P15/P16/RB1/E2F tumour suppressor axis. We also discuss how these methylation changes might occur in the first place - whether in the context of the CpG island methylator phenotype or constitutional DNA methylation. The choice of assay used to measure methylation can have a significant impact on interpretation of methylation states, and some examples where this can influence clinical decision-making are presented. Aberrant DNA methylation patterns in circulating tumour DNA (ctDNA) are also showing great promise in the context of non-invasive cancer detection and monitoring using liquid biopsies; however, caution must be taken in interpreting these results in cases where constitutional methylation may be present. Thus, this review aims to provide researchers and clinicians with a comprehensive summary of this broad, but important subject, illustrating the potentials and pitfalls of assessing aberrant DNA methylation in cancer.

Predicting patient outcomes after treatment with immune checkpoint blockade: A review of biomarkers derived from diverse data modalities

Immune checkpoint blockade (ICB) therapy targeting cytotoxic T-lymphocyte-associated protein 4, programmed death 1, and programmed death ligand 1 has shown durable remission and clinical success across different cancer types. However, patient outcomes vary among disease indications. Studies have identified prognostic biomarkers associated with immunotherapy response and patient outcomes derived from diverse data types, including next-generation bulk and single-cell DNA, RNA, T cell and B cell receptor sequencing data, liquid biopsies, and clinical imaging. Owing to inter- and intra-tumor heterogeneity and the immune system's complexity, these biomarkers have diverse efficacy in clinical trials of ICB. Here, we review the genetic and genomic signatures and image features of ICB studies for pan-cancer applications and specific indications. We discuss the advantages and disadvantages of computational approaches for predicting immunotherapy effectiveness and patient outcomes. We also elucidate the challenges of immunotherapy prognostication and the discovery of novel immunotherapy targets.

Characterization and visualization of tandem repeats at genome scale

Tandem repeat (TR) variation is associated with gene expression changes and numerous rare monogenic diseases. Although long-read sequencing provides accurate full-length sequences and methylation of TRs, there is still a need for computational methods to profile TRs across the genome. Here we introduce the Tandem Repeat Genotyping Tool (TRGT) and an accompanying TR database. TRGT determines the consensus sequences and methylation levels of specified TRs from PacBio HiFi sequencing data. It also reports reads that support each repeat allele. These reads can be subsequently visualized with a companion TR visualization tool. Assessing 937,122 TRs, TRGT showed a Mendelian concordance of 98.38%, allowing a single repeat unit difference. In six samples with known repeat expansions, TRGT detected all expansions while also identifying methylation signals and mosaicism and providing finer repeat length resolution than existing methods. Additionally, we released a database with allele sequences and methylation levels for 937,122 TRs across 100 genomes.

Developing a comprehensive solution aimed to disrupt LARS1/RagD protein-protein interaction

Aminoacyl-tRNA synthetases are crucial enzymes involved in protein synthesis and various cellular physiological reactions. Aside from their standard role in linking amino acids to the corresponding tRNAs, they also impact protein homeostasis by controlling the level of soluble amino acids within the cell. For instance, leucyl-tRNA synthetase (LARS1) acts as a leucine sensor for the mammalian target of rapamycin complex 1 (mTORC1), and may also function as a probable GTPase-activating protein (GAP) for the RagD subunit of the heteromeric activator of mTORC1. In turn, mTORC1 regulates cellular processes, such as protein synthesis, autophagy, and cell growth, and is implicated in various human diseases including cancer, obesity, diabetes, and neurodegeneration. Hence, inhibitors of mTORC1 or a deregulated mTORC1 pathway may offer potential cancer therapies. In this study, we investigated the structural requirements for preventing the sensing and signal transmission from LARS to mTORC1. Building upon recent studies on mTORC1 regulation activation by leucine, we lay the foundation for the development of chemotherapeutic agents against mTORC1 that can overcome resistance to rapamycin. Using a combination of in-silico approaches to develop and validate an alternative interaction model, discussing its benefits and advancements. Finally, we identified a set of compounds ready for testing to prevent LARS1/RagD protein-protein interactions. We establish a basis for creating chemotherapeutic drugs targeting mTORC1, which can conquer resistance to rapamycin. We utilize in-silico methods to generate and confirm an alternative interaction model, outlining its advantages and improvements, and pinpoint a group of novel substances that can prevent LARS1/RagD interactions.Communicated by Ramaswamy H. Sarma.

Cost-effectiveness of pembrolizumab for previously treated MSI-H/dMMR solid tumours in the UK

OBJECTIVES

Patients with previously treated microsatellite instability-high (MSI-H)/mismatch repair deficient (dMMR) tumours have limited chemotherapeutic treatment options. Pembrolizumab received approval from the EMA in 2022 for the treatment of colorectal, endometrial, gastric, small intestine, and biliary MSI-H/dMMR tumour types. This approval was supported by data from the KEYNOTE-164 and KEYNOTE-158 clinical trials. This study evaluated the cost-effectiveness of pembrolizumab compared with standard of care (SoC) for previously treated MSI-H/dMMR solid tumours in line with the approved EMA label from a UK healthcare payer perspective.

METHODS

A multi-tumour partitioned survival model was built consisting of pre-progression, progressed disease, and dead health states. Pembrolizumab survival outcomes were extrapolated using Bayesian hierarchical models (BHMs) fitted to pooled data from KEYNOTE-164 and KEYNOTE-158. Comparator outcomes were informed by published sources. Tumour sites were modelled independently and then combined, weighted by tumour site distribution. A SoC comparator was used to formulate the overall cost-effectiveness result with pembrolizumab as the intervention. SoC comprised a weighted average of the comparators by tumour site based on market share. Drug acquisition, administration, adverse events, monitoring, subsequent treatment, end-of-life costs, and testing costs were included. Sensitivity and scenario analyses were performed, including modelling pembrolizumab efficacy using standard parametric survival models.

RESULTS

Pembrolizumab, at list price, was associated with £129,469 in total costs, 8.30 LYs, and 3.88 QALYs across the pooled tumour sites. SoC was associated with £28,222 in total costs, 1.14 LYs, and 0.72 QALYs across the pooled tumour sites. This yields an incremental cost-effectiveness ratio (ICER) of £32,085 per QALY. Results were robust to sensitivity and scenario analyses.

CONCLUSIONS

This model demonstrates pembrolizumab provides a valuable new alternative therapy for UK patients with MSH-H/dMMR cancer at the cost of £32,085 per QALY, with confidential discounts anticipated to improve cost-effectiveness further.