The therapeutic significance of mutational signatures from DNA repair deficiency in cancer

The cold immunological landscape of ATM-deficient cancers

BACKGROUND

Mutations in genes encoding DNA repair factors, which facilitate mismatch repair, homologous recombination, or DNA polymerase functions, are known to enhance tumor immunogenicity. Ataxia telangiectasia mutated (ATM) is a central regulator of DNA double-strand break repair and is frequently affected by somatic or germline mutations in various cancer types, including breast, prostate, pancreatic, and lung cancer. However, the consequences of ATM loss on tumor immunogenicity are poorly understood.

METHODS

We generated isogenic ATM-null models using CRISPR in murine triple-negative breast (4T1) and colorectal (CT26) cancer cell lines. ATM inactivation was confirmed by PCR and western blot. Immune cell infiltrates were assessed by flow cytometry and immunohistochemistry in both murine tumors and human samples from breast and lung cancers (via The Cancer Genome Atlas and institutional cohorts). In vivo, the impact of ATM loss on tumor growth and response to immune checkpoint blockade (anti-programmed cell death protein-1 (PD-1)) was evaluated. Furthermore, we compared the effects of different DNA-damaging agents-including an ATR inhibitor (RP-3500), a PARP inhibitor (olaparib), and the topoisomerase II inhibitor etoposide-on interferon-stimulated gene (ISG) expression and immune modulation.

RESULTS

We find that-in contrast to other DNA repair defects-ATM deficiency (1) fails to encourage immune effector cell infiltration into tumors, and (2) does not enable immune cell recruitment via synthetic lethality strategies in clinical trials, such as with ATR inhibition. Assessing various DNA-damaging agents in Atm null tumors revealed a differential activation of type I interferon (IFN) signaling, with etoposide, a topoisomerase II inhibitor, emerging as the strongest activator of ISG under these conditions. Yet, PD-1-targeted immune checkpoint blockade does not bolster the therapeutic activity of etoposide in Atm-null syngeneic tumor models, nor does it modify the tumor microenvironment, suggesting that type I IFN signaling alone is insufficient to overcome immunosuppression in immunologically cold ATM null neoplasms.

CONCLUSIONS

ATM deficiency, while compromising DNA repair and enhancing sensitivity to radiation and ATR inhibition, does not increase tumor antigenicity or immunogenicity. Altogether, our results have important implications for the design of novel combination therapies for ATM null tumors and highlight the importance of antigenicity in the immunological consequences of defective DNA repair.

Advancing precision oncology with AI-powered genomic analysis

Multiomics data integration approaches offer a comprehensive functional understanding of biological systems, with significant applications in disease therapeutics. However, the quantitative integration of multiomics data presents a complex challenge, requiring highly specialized computational methods. By providing deep insights into disease-associated molecular mechanisms, multiomics facilitates precision medicine by accounting for individual omics profiles, enabling early disease detection and prevention, aiding biomarker discovery for diagnosis, prognosis, and treatment monitoring, and identifying molecular targets for innovative drug development or the repurposing of existing therapies. AI-driven bioinformatics plays a crucial role in multiomics by computing scores to prioritize available drugs, assisting clinicians in selecting optimal treatments. This review will explain the potential of AI and multiomics data integration for disease understanding and therapeutics. It highlight the challenges in quantitative integration of diverse omics data and clinical workflows involving AI in cancer genomics, addressing the ethical and privacy concerns related to AI-driven applications in oncology. The scope of this text is broad yet focused, providing readers with a comprehensive overview of how AI-powered bioinformatics and integrative multiomics approaches are transforming precision oncology. Understanding bioinformatics in Genomics, it explore the integrative multiomics strategies for drug selection, genome profiling and tumor clonality analysis with clinical application of drug prioritization tools, addressing the technical, ethical, and practical hurdles in deploying AI-driven genomics tools.

Navigating established and emerging biomarkers for immune checkpoint inhibitor therapy

Immune checkpoint inhibitors (ICIs) have improved outcomes of patients with many different cancers. These antibodies target molecules such as programmed cell death 1 (PD-1) or cytotoxic T lymphocyte associated protein 4 (CTLA-4) which normally function to limit immune activity. Treatment with ICIs reactivates T cells to destroy tumor cells in a highly specific manner, which in some patients, results in dramatic remissions and durable disease control. Over the last decade, much effort has been directed at characterizing factors that drive efficacy and resistance to ICI therapy. Food and Drug Administration (FDA)-approved biomarkers for ICI therapy have facilitated more judicious treatment of cancer patients and transformed the field of precision oncology. Yet, adaptive immunity against cancers is complex, and newer data have revealed the potential utility of other biomarkers. In this review, we discuss the utility of currently approved biomarkers and highlight how emerging biomarkers can further improve the identification of patients who benefit from ICIs.

The Role of MSI Testing Methodology and Its Heterogeneity in Predicting Colorectal Cancer Immunotherapy Response

MSI is a crucial biomarker for selecting CRC patients for immunotherapy. Here, we analyze the first results from the observational prospective trial BLOOMSI (NCT06414304), which investigated the impact of MSI/dMMR testing methods and baseline tumor heterogeneity on treatment outcomes. Thirty MSI/dMMR+ CRC patients, who were candidates for immunotherapy, were enrolled. Depending on the local test used for MSI/dMMR, central PCR/IHC was performed. Baseline FFPE and liquid biopsy (LB) were analyzed with NGS. ORR (objective response rate) in the ITT population was 50% (95% CI, 31.3-68.7%). Concordance between local/central dMMR/MSI testing was 81%, and the concordance of IHC, PCR, NGS/FFPE, and NGS/LB was 68.4%. The ORR was similar for IHC+, PCR+, NGS/FFPE+, and NGS/LB+ patients (55.6%, 55.6%, 55%, and 57.9%, respectively). The ORR among patients with discordant IHC/PCR results was 0%, and the ORR among patients with NGS/LB-ORR was 25% (2/8 CR). Next, we performed quantitative MSI analysis, reflecting the clonality of MSI+ tumor cells. Multivariate analysis identified MSI clonality in FFPE (HR 0.63, 95% CI, 0.39-0.99, p = 0.0487) and LB (HR 3.05, 95% CI, 2.01-4.65, p < 0.00001) as independent predictors of progression. The ORR in patients with high clonality (≥7%, n = 4, NGS/LB) was 25%. We describe baseline methodological predictors of non-response to immunotherapy and propose a strategy for selecting potential non-responders. These findings warrant further investigation.

Allele and genotype frequencies of variants in P450 cytochromes, transports, and DNA repair enzymes in the Dominican Republic population

Introduction

Single-nucleotide variants (SNVs) give rise to important inter-individual and inter-ethnic variabilities in the metabolism and disposition of several therapeutic agents and may cause differences in the treatment response to clinically important drugs like antiarrhythmics, antidepressants, antihistamines, and antipsychotics, among others. Information about the prevalence of variants in the Dominican Republic population is still limited. The aim of this study was to describe the frequency distribution of 32 SNVs from 14 genes with pharmacogenetic interest within a sample of 150 unrelated healthy individuals.

Methods

Genotype and allele frequencies were determined, and pairwise Wright's FST statistic was evaluated.

Results

Hardy-Weinberg equilibrium deviations were found in seven loci from CYP2D6 (rs16947, rs3892097, rs1058164, rs1135840, and rs28371725) and CYP2C19 (rs12769205 and rs4244285) genes. The minor allele frequencies ranged from 0.01 to 0.50 values in the xenobiotic biotransformation enzymes and transporter genes. The average admixture estimates were 51.6%, 39.5%, and 8.9% for European, African, and Amerindian ancestries, respectively. Pairwise FST analysis revealed that Dominicans displayed genetic similarity to Latin American populations, especially those with Afro-Caribbean ancestry, given the selected variants. Higher differences were identified from East and South Asians, Europeans, and Africans, in which several values above the FST threshold for moderate differentiation were identified within variants in CYP2C, CYP3A, CYP1A1, ABCB1, SLC45A2, XRCC1, and XRCC3 genes.

Conclusions

These results should allow establishing the clinical relevance of pharmacogenetic testing in variant alleles related to drug transport and metabolism genes in this population.

Increased Synthetic Cytotoxicity of Combinatorial Chemoradiation Therapy in Homologous Recombination Deficient Tumors

PURPOSE

Homologous recombination deficient (HRD) tumors are exquisitely sensitive to platinum-based chemotherapy and when combined with radiation therapy (RT), leads to improved overall survival in multiple cancer types. Whether a subset of tumors with distinct molecular characteristics demonstrate increased benefit from cisplatin and RT (c-RT) is unclear. We hypothesized that HRD tumors, whether associated with BRCA mutations or genomic scars of HRD, exhibit exquisite sensitivity to c-RT, and that HRD may be a significant driver of c-RT benefit.

METHODS AND MATERIALS

Sensitivity to c-RT was examined using isogenic and sporadic breast cancer cell lines. HRD was assessed using 4 assays: RT-induced Rad51 foci, a DR-GFP reporter assay, a genomic scar score (large-scale state transitions [LST]), and clonogenic survival assays. Whole-genome sequencing of 4 breast tumors from a phase 2 clinical trial of neoadjuvant c-RT in triple-negative breast cancer was performed and HRD was defined using HRDetect.

RESULTS

BRCA1/2 deficient cell lines displayed functional HRD based on the Rad51 functional assay, with c-RT to RT or cisplatin interaction ratios (IR) of 1.11 and 26.84 for the BRCA1 isogenic pair at 2 μM cisplatin and 6 Gy, respectively. The highest LST lines demonstrated HRD and synthetic cytotoxicity to c-RT with IR at 2 Gy and cisplatin 20 μM of 7.50, and the lowest LST line with IR of 0.65. Of 4 evaluable patients in the phase 2 trial, one achieved a pathologic complete response with corresponding HRD based on multiple genomic scar scores including HRDetect and LST scores, compared with patients without a pathologic complete response.

CONCLUSIONS

HRD breast cancers, whether identified by BRCA1/2 mutation status, functional tests, or mutational signatures, appear to be significantly more sensitive to c-RT compared with isogenic controls or tumors without HRD mutational signatures. HRD tumors may be exquisitely sensitive to c-RT which warrants further clinical investigation to guide a precision oncology approach.

Inferring active mutational processes in cancer using single cell sequencing and evolutionary constraints

Ongoing mutagenesis in cancer drives genetic diversity throughout the natural history of cancers. As the activities of mutational processes are dynamic throughout evolution, distinguishing the mutational signatures of 'active' and 'historical' processes has important implications for studying how tumors evolve. This can aid in understanding mutagenic states at the time of presentation, and in associating active mutational process with therapeutic resistance. As bulk sequencing primarily captures historical mutational processes, we studied whether ultra-low-coverage single-cell whole-genome sequencing (scWGS), which measures the distribution of mutations across hundreds or thousands of individual cells, could enable the distinction between historical and active mutational processes. While technical challenges and data sparsity have limited mutation analysis in scWGS, we show that these data contain valuable information about dynamic mutational processes. To robustly interpret single nucleotide variants (SNVs) in scWGS, we introduce ArtiCull, a method to identify and remove SNV artifacts by leveraging evolutionary constraints, enabling reliable detection of mutations for signature analysis. Applying this approach to scWGS data from pancreatic ductal adenocarcinoma (PDAC), triple-negative breast cancer (TNBC), and high-grade serous ovarian cancer (HGSOC), we uncover temporal and spatial patterns in mutational processes. In PDAC, we observe a temporal increase in mismatch repair deficiency (MMRd). In cisplatin-treated TNBC patient-derived xenografts, we identify therapy-induced mutagenesis and inactivation of APOBEC3 activity. In HGSOC, we show distinct patterns of APOBEC3 mutagenesis, including late tumor-wide activation in one case and clade-specific enrichment in another. Additionally, we detect a clone-specific increase in SBS17 activity, in a clone previously linked to recurrence. Our findings establish ultra-low-coverage scWGS as a powerful approach for studying active mutational processes that may influence ongoing clonal evolution and therapeutic resistance.

AZD1390, an Ataxia telangiectasia mutated inhibitor, enhances cisplatin mediated apoptosis in breast cancer cells

Genomic instability is often caused by deficiencies in DNA damage repair pathways, making therapeutic targeting of DDR beneficial for cancer patients with specific DDR functions. ATM kinase plays a critical role in various cellular processes and its deficiency increases sensitivity to DDR-targeted agents in different cancers. Recent studies highlight ATM inhibition as a potential clinical target, with AZD1390 being a notable ATM inhibitor due to its potent and selective inhibition, ability to accumulate at DNA breaks. The study aimed to evaluate the potential anti-cancer effects of AZD1390, a key component of the DNA damage response, in breast cancer cells. The impact of the combination of AZD1390 and cisplatin on various parameters such as cell viability, proliferation, colony formation capacity, DNA damage, reactive oxygen species (ROS) levels, mitochondrial membrane potential, cell cycle progression, and cell death in breast cancer cells was evaluated using several methodologies, including WST-1 assays, real-time cell analysis, colony formation assays, comet assays, DCF-DA, MMP/JC-1 staining assays, flow cytometry along with Western blot analysis. We found that AZD1390 and cisplatin displayed synergistic antitumor effects in breast cancer cells at low doses. Addinationaly exhibited significant anti-proliferative effects in colony formation and real-time cell proliferation experiments, increasing intracellular ROS levels and mitochondrial membrane potential.The combined treatment also arrested the cell cycle at the G2-M point. Furthermore, combination of AZD1390 with cisplatin enhances its apoptotic effects in MCF-7 and MDA-MB-231 cells. These findings could aid in developing new treatments for breast cancer that exploit the genomic instability of cancer cells.

The multifaceted roles of aldolase A in cancer: glycolysis, cytoskeleton, translation and beyond

Cancer, a complicated disease characterized by aberrant cellular metabolism, has emerged as a formidable global health challenge. Since the discovery of abnormal aldolase A (ALDOA) expression in liver cancer for the first time, its overexpression has been identified in numerous cancers, including colorectal cancer (CRC), breast cancer (BC), cervical adenocarcinoma (CAC), non-small cell lung cancer (NSCLC), gastric cancer (GC), hepatocellular carcinoma (HCC), pancreatic cancer adenocarcinoma (PDAC), and clear cell renal cell carcinoma (ccRCC). Moreover, ALDOA overexpression promotes cancer cell proliferation, invasion, migration, and drug resistance, and is closely related to poor prognosis of patients with cancer. Although originally discovered to promote cancer initiation and progression by accelerating glycolysis, recent studies have revealed its atypical roles in cancer, e.g., adjusting cytoskeleton, regulating mRNA translation, cell signaling pathways, and DNA repair. These aforementioned findings challenge our traditional understanding of ALDOA function and prompt deep exploration of its novel roles in tumor biology. The present review summarizes the latest insights into ALDOA as a potential cancer biomarker and therapeutic target.

RNA sequencing comparing centenarian and middle-aged women lymphoblastoid cell lines identifies age-related dysregulated expression of genes encoding selenoproteins, heat shock proteins, CD99, and BID

Women typically live longer than men, and constitute the majority of centenarians. We applied RNA-sequencing (RNA-seq) of blood-derived lymphoblastoid cell lines (LCLs) from women aged 60-80 years and centenarians (100-105 years), validated the RNA-seq findings by real-time PCR, and additionally measured the differentially expressed genes in LCLs from young women aged 20-35 years. Top RNA-seq genes with differential expression between the age groups included three selenoproteins (GPX1, SELENOW, SELENOH) and three heat shock proteins (HSPA6, HSPA1A, HSPA1B), with the highest expression in LCLs from young women, indicating that young women are better protected from oxidative stress. The expression of two additional genes, BID encoding BH3-interacting domain death agonist and CD99 encoding CD99 antigen, showed unique age dependence, with similar expression levels in young and centenarian women while exhibiting higher and lower expression levels, respectively, in LCLs from women aged 60-80 years compared with the two other age groups. This age-related differential expression of BID and CD99 suggests elevated inflammation susceptibility in middle-aged women compared with either young or centenarian women. Our findings, once validated with human peripheral blood mononuclear cells and further cell types, may lead to novel healthy aging diagnostics and therapeutics.

Mechanism of immune activation mediated by genomic instability and its implication in radiotherapy combined with immune checkpoint inhibitors

Various genetic and epigenetic changes associated with genomic instability (GI), including DNA damage repair defects, chromosomal instability, and mitochondrial GI, contribute to development and progression of cancer. These alterations not only result in DNA leakage into the cytoplasm, either directly or through micronuclei, but also trigger downstream inflammatory signals, such as the cyclic GMP-AMP synthase (cGAS)-stimulator of interferon genes (STING) signaling pathway. Apart from directly inducing DNA damage to eliminate cancer cells, radiotherapy (RT) exerts its antitumor effects through intracellular DNA damage sensing mechanisms, leading to the activation of downstream inflammatory signaling pathways. This not only enables local tumor control but also reshapes the immune microenvironment, triggering systemic immune responses. The combination of RT and immunotherapy has emerged as a promising approach to increase the probability of abscopal effects, where distant tumors respond to treatment due to the systemic immunomodulatory effects. This review emphasizes the importance of GI in cancer biology and elucidates the mechanisms by which RT induces GI remodeling of the immune microenvironment. By elucidating the mechanisms of GI and RT-induced immune responses, we aim to emphasize the crucial importance of this approach in modern oncology. Understanding the impact of GI on tumor biological behavior and therapeutic response, as well as the possibility of activating systemic anti-tumor immunity through RT, will pave the way for the development of new treatment strategies and improve prognosis for patients.

STING Promotes the Progression of ADPKD by Regulating Mitochondrial Function, Inflammation, Fibrosis, and Apoptosis

Autosomal dominant polycystic kidney disease (ADPKD) is a predominant genetic disease, which is caused by mutations in PKD genes and is associated with DNA damage in cystic cells. The intrinsic stimulator of interferon genes (STING) pathway is crucial for recognizing damaged DNA in the cytosol, triggering the expression of inflammatory cytokines to activate defense mechanisms. However, the precise roles and mechanisms of STING in ADPKD remain elusive. In this study, we show that Pkd1 mutant mouse kidneys show upregulation of STING, which is stimulated by the DNAs of nuclear and mitochondrial origin. The activation of STING promotes cyst growth through increasing (1) the activation of NF-κB in Pkd1 mutant cells and (2) the recruitment of macrophages in the interstitial and peri-cystic regions in Pkd1 mutant mouse kidneys via NF-κB mediating the upregulation of TNF-α and MCP-1. Targeting STING with its specific inhibitor C-176 delays cyst growth in an early-stage aggressive Pkd1 conditional knockout mouse model and a milder long-lasting Pkd1 mutant mouse model. Targeting STING normalizes mitochondrial structure and function, decreases the formation of micronuclei, induces Pkd1 mutant renal epithelial cell death via p53 signaling, and decreases renal fibrosis in Pkd1 mutant mouse kidneys. These results support that STING is a novel therapeutic target for ADPKD treatment.

Cancer mutational signatures identification in clinical assays using neural embedding-based representations

While mutational signatures provide a plethora of prognostic and therapeutic insights, their application in clinical-setting, targeted gene panels is extremely limited. We develop a mutational representation model (which learns and embeds specific mutation signature connections) that enables prediction of dominant signatures with only a few mutations. We predict the dominant signatures across more than 60,000 tumors with gene panels, delineating their landscape across different cancers. Dominant signature predictions in gene panels are of clinical importance. These included UV, tobacco, and apolipoprotein B mRNA editing enzyme, catalytic polypeptide (APOBEC) signatures that are associated with better survival, independently from mutational burden. Further analyses reveal gene and mutation associations with signatures, such as SBS5 with TP53 and APOBEC with FGFR3S249C. In a clinical use case, APOBEC signature is a robust and specific predictor for resistance to epidermal growth factor receptor-tyrosine kinase inhibitors (EGFR-TKIs). Our model provides an easy-to-use way to detect signatures in clinical setting assays with many possible clinical implications for an unprecedented number of cancer patients.

Developmental origins shape the paediatric cancer genome

In the past two decades, technological advances have brought unprecedented insights into the paediatric cancer genome revealing characteristics distinct from those of adult cancer. Originating from developing tissues, paediatric cancers generally have low mutation burden and are driven by variants that disrupt the transcriptional activity, chromatin state, non-coding cis-regulatory regions and other biological functions. Within each tumour, there are multiple populations of cells with varying states, and the lineages of some can be tracked to their fetal origins. Genome-wide genetic screening has identified vulnerabilities associated with both the cell of origin and transcription deregulation in paediatric cancer, which have become a valuable resource for designing new therapeutic approaches including those for small molecules, immunotherapy and targeted protein degradation. In this Review, we present recent findings on these facets of paediatric cancer from a pan-cancer perspective and provide an outlook on future investigations.

MUSE-XAE: MUtational Signature Extraction with eXplainable AutoEncoder enhances tumour types classification

MOTIVATION

Mutational signatures are a critical component in deciphering the genetic alterations that underlie cancer development and have become a valuable resource to understand the genomic changes during tumorigenesis. Therefore, it is essential to employ precise and accurate methods for their extraction to ensure that the underlying patterns are reliably identified and can be effectively utilized in new strategies for diagnosis, prognosis, and treatment of cancer patients.

RESULTS

We present MUSE-XAE, a novel method for mutational signature extraction from cancer genomes using an explainable autoencoder. Our approach employs a hybrid architecture consisting of a nonlinear encoder that can capture nonlinear interactions among features, and a linear decoder which ensures the interpretability of the active signatures. We evaluated and compared MUSE-XAE with other available tools on both synthetic and real cancer datasets and demonstrated that it achieves superior performance in terms of precision and sensitivity in recovering mutational signature profiles. MUSE-XAE extracts highly discriminative mutational signature profiles by enhancing the classification of primary tumour types and subtypes in real world settings. This approach could facilitate further research in this area, with neural networks playing a critical role in advancing our understanding of cancer genomics.

AVAILABILITY AND IMPLEMENTATION

MUSE-XAE software is freely available at https://github.com/compbiomed-unito/MUSE-XAE.

Mismatch Repair Deficiency as a Predictive and Prognostic Biomarker in Endometrial Cancer: A Review on Immunohistochemistry Staining Patterns and Clinical Implications

Among the four endometrial cancer (EC) TCGA molecular groups, the MSI/hypermutated group represents an important percentage of tumors (30%), including different histotypes, and generally confers an intermediate prognosis for affected women, also providing new immunotherapeutic strategies. Immunohistochemistry for MMR proteins (MLH1, MSH2, MSH6 and PMS2) has become the optimal diagnostic MSI surrogate worldwide. This review aims to provide state-of-the-art knowledge on MMR deficiency/MSI in EC and to clarify the pathological assessment, interpretation pitfalls and reporting of MMR status.

Genome scale CRISPR screens identify actin capping proteins as key modulators of therapeutic responses to radiation and immunotherapy

Radiotherapy (RT), is a fundamental treatment for malignant tumors and is used in over half of cancer patients. As radiation can promote anti-tumor immune effects, a promising therapeutic strategy is to combine radiation with immune checkpoint inhibitors (ICIs). However, the genetic determinants that impact therapeutic response in the context of combination therapy with radiation and ICI have not been systematically investigated. To unbiasedly identify the tumor intrinsic genetic factors governing such responses, we perform a set of genome-scale CRISPR screens in melanoma cells for cancer survival in response to low-dose genotoxic radiation treatment, in the context of CD8 T cell co-culture and with anti-PD1 checkpoint blockade antibody. Two actin capping proteins, Capza3 and Capg, emerge as top hits that upon inactivation promote the survival of melanoma cells in such settings. Capza3 and Capg knockouts (KOs) in mouse and human cancer cells display persistent DNA damage due to impaired homology directed repair (HDR); along with increased radiation, chemotherapy, and DNA repair inhibitor sensitivity. However, when cancer cells with these genes inactivated were exposed to sublethal radiation, inactivation of such actin capping protein promotes activation of the STING pathway, induction of inhibitory CEACAM1 ligand expression and resistance to CD8 T cell killing. Patient cancer genomics analysis reveals an increased mutational burden in patients with inactivating mutations in CAPG and/or CAPZA3, at levels comparable to other HDR associated genes. There is also a positive correlation between CAPG expression and activation of immune related pathways and CD8 T cell tumor infiltration. Our results unveil the critical roles of actin binding proteins for efficient HDR within cancer cells and demonstrate a previously unrecognized regulatory mechanism of therapeutic response to radiation and immunotherapy.

DNA repair deficiency and the immune microenvironment: A pathways perspective

Timely and accurate repair of DNA damage is required for genomic stability, but DNA repair pathways are often lost or altered in tumors. In addition to directly impacting tumor cell response to DNA damage, DNA repair deficiency can also alter the immune microenvironment via changes in innate and adaptive immune signaling. In some settings, these changes can lead to increased sensitivity to immune checkpoint inhibitors (ICIs). In this review, we discuss the impact of specific DNA repair pathway dysfunction on immune contexture and ICI response in solid tumors.

The fructose-bisphosphate, Aldolase A (ALDOA), facilitates DNA-PKcs and ATM kinase activity to regulate DNA double-strand break repair

Glucose metabolism and DNA repair are fundamental cellular processes frequently dysregulated in cancer. In this study, we define a direct role for the glycolytic Aldolase A (ALDOA) protein in DNA double-strand break (DSB) repair. ALDOA is a fructose biphosphate Aldolase that catalyses fructose-1,6-bisphosphate to glyceraldehyde 3-phosphate (G3P) and dihydroxyacetone phosphate (DHAP), during glycolysis. Here, we show that upon DNA damage induced by ionising radiation (IR), ALDOA translocates from the cytoplasm into the nucleus, where it partially co-localises with the DNA DSB marker γ-H2AX. DNA damage was shown to be elevated in ALDOA-depleted cells prior to IR and following IR the damage was repaired more slowly. Consistent with this, cells depleted of ALDOA exhibited decreased DNA DSB repair via non-homologous end-joining and homologous recombination. In support of the defective repair observed in its absence, ALDOA was found to associate with the major DSB repair effector kinases, DNA-dependent Protein Kinase (DNA-PK) and Ataxia Telangiectasia Mutated (ATM) and their autophosphorylation was decreased when ALDOA was depleted. Together, these data establish a role for an essential metabolic protein, ALDOA in DNA DSB repair and suggests that targeting ALDOA may enable the concurrent targeting of cancer metabolism and DNA repair to induce tumour cell death.

Commonalities and differences in the mutational signature and somatic driver mutation landscape across solid and hollow viscus organs

Advances in sequencing have revealed a highly variegated landscape of mutational signatures and somatic driver mutations in a range of normal tissues. Normal tissues accumulate mutations at varying rates ranging from 11 per cell per year in the liver, to 1879 per cell per year in the bladder. In addition, some normal tissues are also comprised of a large proportion of cells which possess driver mutations while appearing phenotypically normal, as in the oesophagus where a majority of cells harbour driver mutations. Individual tissue proliferation and mutation rate, unique mutagenic stimuli, and local tissue architecture contribute to this highly variegated landscape which confounds the functional characterization of driver mutations found in normal tissue. In particular, our understanding of the relationship between normal tissue somatic mutations and tumour initiation or future cancer risk remains poor. Here, we describe the mutational signatures and somatic driver mutations in solid and hollow viscus organs, highlighting unique characteristics in a tissue-specific manner, while simultaneously seeking to describe commonalities which can bring forward a basic unified theory on the role of these driver mutations in tumour initiation. We discuss novel findings which can be used to inform future research in this field.

Long-molecule scars of backup DNA repair in BRCA1- and BRCA2-deficient cancers

Homologous recombination (HR) deficiency is associated with DNA rearrangements and cytogenetic aberrations1. Paradoxically, the types of DNA rearrangements that are specifically associated with HR-deficient cancers only minimally affect chromosomal structure2. Here, to address this apparent contradiction, we combined genome-graph analysis of short-read whole-genome sequencing (WGS) profiles across thousands of tumours with deep linked-read WGS of 46 BRCA1- or BRCA2-mutant breast cancers. These data revealed a distinct class of HR-deficiency-enriched rearrangements called reciprocal pairs. Linked-read WGS showed that reciprocal pairs with identical rearrangement orientations gave rise to one of two distinct chromosomal outcomes, distinguishable only with long-molecule data. Whereas one (cis) outcome corresponded to the copying and pasting of a small segment to a distant site, a second (trans) outcome was a quasi-balanced translocation or multi-megabase inversion with substantial (10 kb) duplications at each junction. We propose an HR-independent replication-restart repair mechanism to explain the full spectrum of reciprocal pair outcomes. Linked-read WGS also identified single-strand annealing as a repair pathway that is specific to BRCA2 deficiency in human cancers. Integrating these features in a classifier improved discrimination between BRCA1- and BRCA2-deficient genomes. In conclusion, our data reveal classes of rearrangements that are specific to BRCA1 or BRCA2 deficiency as a source of cytogenetic aberrations in HR-deficient cells.

MMR profile and microsatellite instability status in colorectal mucinous adenocarcinoma with synchronous metastasis: a new clue for the clinical practice

AIMS

Mucinous adenocarcinoma (MA) is associated with a high frequency of microsatellite instability (MSI). In the metastatic setting, it is crucial to establish mismatch repair (MMR) and/or MSI status. However, genetic heterogeneity between primary tumour and synchronous metastasis and the diagnostic accuracy of the assay may hamper the MMR/MSI status evaluation.

METHODS

In this study, we assessed the concordance rate of the MMR/MSI status between primary tumour and paired synchronous metastasis of 25 MAs. MMR status was evaluated by immunohistochemistry (IHC), while MSI status was evaluated by using three different molecular approaches: microfluidic electrophoresis of PCR products (TapeStation 4200 platform), full-closed RTqPCR system (Idylla system) and multiplex amplification with fluorescent primers and subsequent DNA fragment analysis on an automated sequencer (Titano MSI test).

RESULTS

The concordance rate between primary MA and metastasis was 21/21 (100%), 23/25 (92.0%), 23/25 (92.0%) and 21/25 (84%) by using IHC, Idylla system, Titano MSI test and TapeStation 4200 system. All the four methods used in our study displayed high concordant rate, ranging from 91.0% (IHC vs Tapestation 4200 platform) to 98.0% (IHC vs Titano).

CONCLUSIONS

Several methodologies are frequently adopted in routine practice to successfully perform MMR/MSI status analysis. The most relevant issues related to MMR/MSI status analysis in MAs concern with low percentage of neoplastic cell and abundant mucine that may affect the molecular analysis. Thus, it might be useful to acquire both primary and metastatic sample to evaluate the MMR/MSI status by integrating IHC evaluation and molecular methodologies to successfully perform molecular profiling for MA patients.

Relationship between homologous recombination deficiency and clinical features of breast cancer based on genomic scar score

BACKGROUND

Homologous recombination deficiency (HRD) phenotype will sensitize tumors to poly (ADP-ribose) polymerases inhibitors and platinum. However, previous studies did not focus on the prevalence of HRD among Chinese breast cancer (BC) patients.

METHODS

One hundred and forty-seven BC patients were included in this study. Their HRD status was assessed by Genomic Scar Score (GSS), which was determined according to the length, site, and type of copy number. HRD was defined as positive when a harmful BRCA1/2 mutation was detected or GSS ≥50.

RESULTS

Our data revealed that 9.5% of the 147 patients tested positive for BRCA1/2 mutation, while approximately 34.7% were HRD-positive. For triple negative BC (TNBC), HRD positivity rate (60.5%) was higher than Luminal A (5.3%), Luminal B (HER2-) (28.8%), and Luminal B (HER2+) (31.6%) subgroups. HRD-positive tumors were more likely to be ER/PR-negative and exhibited higher Ki-67 expression. 50.0% of the HRD-positive patients achieved pathologic complete remission (pCR) after neoadjuvant therapy. HRD-positive patients tended to have a higher risk for cancer recurrence or metastasis compared to HRD-negative patients (29.4% vs. 13.5%).

CONCLUSION

We investigated the HRD status among Chinese BC patients using an HRD detection tool developed based on the Chinese population. The clinical characteristics, pathological profile, family history pattern, neoadjuvant efficacy, and disease progression events of HRD-positive and negative patients were described and compared. Thus, our data provided an evidence-based basis for applying the original HRD assay in Chinese BC.

The APE2 nuclease is essential for DNA double-strand break repair by microhomology-mediated end joining

Microhomology-mediated end joining (MMEJ) is an intrinsically mutagenic pathway of DNA double-strand break (DSB) repair essential for proliferation of homologous recombination (HR)-deficient tumors. Although targeting MMEJ has emerged as a powerful strategy to eliminate HR-deficient (HRD) cancers, this is limited by an incomplete understanding of the mechanism and factors required for MMEJ repair. Here, we identify the APE2 nuclease as an MMEJ effector. We show that loss of APE2 inhibits MMEJ at deprotected telomeres and at intra-chromosomal DSBs and is epistatic with Pol Theta for MMEJ activity. Mechanistically, we demonstrate that APE2 possesses intrinsic flap-cleaving activity, that its MMEJ function in cells depends on its nuclease activity, and further identify an uncharacterized domain required for its recruitment to DSBs. We conclude that this previously unappreciated role of APE2 in MMEJ contributes to the addiction of HRD cells to APE2, which could be exploited in the treatment of cancer.

Integrative analysis of TP53 mutations in lung adenocarcinoma for immunotherapies and prognosis

BACKGROUND

The TP53 tumor suppressor gene is one of the most mutated genes in lung adenocarcinoma (LUAD) and plays a vital role in regulating the occurrence and progression of cancer. We aimed to elucidate the association between TP53 mutations, response to immunotherapies and the prognosis of LUAD.

METHODS

Genomic, transcriptomic, and clinical data of LUAD were downloaded from The Cancer Genome Atlas (TCGA) dataset. Gene ontology (GO) analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis, gene set enrichment analysis (GSEA). Gene set variation analysis (GSVA) were performed to determine the differences in biological pathways. A merged protein-protein interaction (PPI) network was constructed and analyzed. MSIpred was used to analyze the correlation between the expression of the TP53 gene, tumor mutation burden (TMB) and tumor microsatellite instability (MSI). CIBERSORT was used to calculate the abundance of immune cells. Univariate and multivariate Cox regression analyses were used to determine the prognostic value of TP53 mutations in LUAD.

RESULTS

TP53 was the most frequently mutated in LUAD, with a mutational frequency of 48%. GO and KEGG enrichment analysis, GSEA, and GSVA results showed a significant upregulation of several signaling pathways, including PI3K-AKT mTOR (P < 0.05), Notch (P < 0.05), E2F target (NES = 1.8, P < 0.05), and G2M checkpoint (NES = 1.7, P < 0.05). Moreover, we found a significant correlation between T cells, plasma cells, and TP53 mutations (R² < 0.01, P = 0.040). Univariate and multivariate Cox regression analyses revealed that the survival prognosis of LUAD patients was related to TP53 mutations (Hazard Ratio (HR) = 0.72 [95% CI, 0.53 to 0.98], P < 0.05), cancer status (P < 0.05), and treatment outcomes (P < 0.05). Lastly, the Cox regression models showed that TP53 exhibited good power in predicting three- and five-year survival rates.

CONCLUSIONS

TP53 may be an independent predictor of response to immunotherapy in LUAD, and patients with TP53 mutations have higher immunogenicity and immune cell infiltration.

Microsatellite Instability: A Review of Molecular Epidemiology and Implications for Immune Checkpoint Inhibitor Therapy

Microsatellite instability (MSI) is one of the most important molecular characteristics of a tumor, which occurs among various tumor types. In this review article, we examine the molecular characteristics of MSI tumors, both sporadic and Lynch-associated. We also overview the risks of developing hereditary forms of cancer and potential mechanisms of tumor development in patients with Lynch syndrome. Additionally, we summarize the results of major clinical studies on the efficacy of immune checkpoint inhibitors for MSI tumors and discuss the predictive role of MSI in the context of chemotherapy and checkpoint inhibitors. Finally, we briefly discuss some of the underlying mechanisms causing therapy resistance in patients treated with immune checkpoint inhibitors.

Analysis of evolutionary dynamics and clonal architecture in prostate cancer

The extent to which clinical and genomic characteristics associate with prostate cancer clonal architecture, tumor evolution, and therapeutic response remains unclear. Here, we reconstructed the clonal architecture and evolutionary trajectories of 845 prostate cancer tumors with harmonized clinical and molecular data. We observed that tumors from patients who self-reported as Black had more linear and monoclonal architectures, despite these men having higher rates of biochemical recurrence. This finding contrasts with prior observations relating polyclonal architecture to adverse clinical outcomes. Additionally, we utilized a novel approach to mutational signature analysis that leverages clonal architecture to uncover additional cases of homologous recombination and mismatch repair deficiency in primary and metastatic tumors and link the origin of mutational signatures to specific subclones. Broadly, prostate cancer clonal architecture analysis reveals novel biological insights that may be immediately clinically actionable and provide multiple opportunities for subsequent investigation.

Statement of significance

Tumors from patients who self-reported as Black demonstrate linear and monoclonal evolutionary trajectories yet experience higher rates of biochemical recurrence. In addition, analysis of clonal and subclonal mutational signatures identifies additional tumors with potentially actionable alterations such as deficiencies in mismatch repair and homologous recombination.

DNA Repair Deficiency Regulates Immunity Response in Cancers: Molecular Mechanism and Approaches for Combining Immunotherapy

Defects in DNA repair pathways can lead to genomic instability in multiple tumor types, which contributes to tumor immunogenicity. Inhibition of DNA damage response (DDR) has been reported to increase tumor susceptibility to anticancer immunotherapy. However, the interplay between DDR and the immune signaling pathways remains unclear. In this review, we will discuss how a deficiency in DDR affects anti-tumor immunity, highlighting the cGAS-STING axis as an important link. We will also review the clinical trials that combine DDR inhibition and immune-oncology treatments. A better understanding of these pathways will help exploit cancer immunotherapy and DDR pathways to improve treatment outcomes for various cancers.

Development and validation of a prognostic model for HER2-low breast cancer to evaluate neoadjuvant therapy

Background

Human epidermal growth factor receptor 2 (HER2) low breast cancer (BC) accounts for 30-51% of all BCs. How to precisely assess the response to neoadjuvant therapy in this heterogenous tumor is currently unanswered. With the advance in multi-omics, refining the molecular subtyping other than the current hormone receptor (HR)-based subtyping to guide the neoadjuvant therapy for HER2-low BC is potentially feasible.

Methods

The messenger RNA (mRNA), clinical, and pathological data of all HER2-low BC patients (n=368) from the Neoadjuvant I-SPY2 Trial, were retrieved. Ninety-eight patients achieved pathological complete response (pCR) were randomly divided into the training and validation sets with 8:2 ratio. The non-pCR cases were corporated into the above datasets with 1:1 ratio. The rest non-pCR cases were served as the test set. Random forest (RF), support vector machine (SVM), and fully connected neural network (FCNN) were applied to establish a 1-dimensional (1D) model based on mRNA data. The method with best prediction value among the 3 models was selected for further modeling when combining pathological features. A new classification of deep learning (CDn) was proposed based on a multi-omics model. After identifying pCR-related features by the integral gradient and unsupervised hierarchical clustering method, the responses to neoadjuvant therapy associated with these features across different subgroups were analyzed.

Results

Compared with the RF and SVM models, the FCNN model achieved the best performance [area under the curve (AUC): 0.89] based on the mRNA feature. By combining mRNA and pathological features, the FCNN model proposed 2 new subtypes including CD1 and CD0 for HER2-low BC. CD1 increased the sensitivity to predict pCR by 23.5% [to 87.8%; 95% confidence interval (CI): 78% to 94%] and improved the specificity to pCR by 12.2% (to 77.4%; 95% CI: 69% to 87%) when comparing with the current HR classification for HER2-low BC.

Conclusions

The new typing method (CD1 and CD0) proposed in this study achieved excellent performance for predicting the pCR to neoadjuvant therapy in HER2-low BC. The patients who were not sensitive to neoadjuvant therapy according to multi-omics models might receive surgical treatment directly.

A Focused Review on Molecular Signalling Mechanisms of Ginsenosides Anti-Lung Cancer and Anti-inflammatory Activities

BACKGROUND

Ginseng (Panax ginseng Meyer) is a cultivated medicinal herb that has been widely available in the Asian region since the last century. Ginseng root is used worldwide in Oriental medicine. Currently, the global mortality and infection rates for lung cancer and inflammation are significantly increasing. Therefore, various preventative methods related to the activity of ginsenosides have been used for lung cancer as well as inflammation.

METHODS

Web-based searches were performed on Web of Science, Springer, PubMed, and Scopus. A cancer statistical analysis was also conducted to show the current ratio of affected cases and death from lung cancer around the world.

RESULTS

Ginsenosides regulate the enzymes that participate in tumor growth and migration, such as nuclear factor kappa B (NF-κB), mitogen-activated protein kinase (p38 MAPK), c-Jun N-terminal kinase (JNK), extracellular signalregulated kinases 1/2 (ERK1/2), the gelatinase network metalloproteinase-2 (MMP-2/9) and activator protein 1 (AP-1). In addition, ginsenosides also possess anti-inflammatory effects by inhibiting the formation of proinflammatory cytokines (tumor necrosis factor-α) (TNF-α) and interleukin-1β (IL-1β) and controlling the activities of inflammatory signalling pathways, such as NF-κB, Janus kinase2/signal transducer, and activator of transcription 3 (Jak2/Stat3).

CONCLUSION

In several in vitro and in vivo models, P. ginseng showed potential beneficial effects in lung cancer and inflammation treatment. In this review, we provide a detailed and up-to-date summary of research evidence for antilung cancer and anti-inflammatory protective effects of ginsenosides and their potential molecular mechanisms.

Proteomic analysis predicts anti-angiogenic resistance in recurred glioblastoma

BACKGROUND

Recurrence is common in glioblastoma multiforme (GBM) because of the infiltrative, residual cells in the tumor margin. Standard therapy for GBM consists of surgical resection followed by chemotherapy and radiotherapy, but the median survival of GBM patients remains poor (~ 1.5 years). For recurrent GBM, anti-angiogenic treatment is one of the common treatment approaches. However, current anti-angiogenic treatment modalities are not satisfactory because of the resistance to anti-angiogenic agents in some patients. Therefore, we sought to identify novel prognostic biomarkers that can predict the therapeutic response to anti-angiogenic agents in patients with recurrent glioblastoma.

METHODS

We selected patients with recurrent GBM who were treated with anti-angiogenic agents and classified them into responders and non-responders to anti-angiogenic therapy. Then, we performed proteomic analysis using liquid-chromatography mass spectrometry (LC-MS) with formalin-fixed paraffin-embedded (FFPE) tissues obtained from surgical specimens. We conducted a gene-ontology (GO) analysis based on protein abundance in the responder and non-responder groups. Based on the LC-MS and GO analysis results, we identified potential predictive biomarkers for anti-angiogenic therapy and validated them in recurrent glioblastoma patients.

RESULTS

In the mass spectrometry-based approach, 4957 unique proteins were quantified with high confidence across clinical parameters. Unsupervised clustering analysis highlighted distinct proteomic patterns (n = 269 proteins) between responders and non-responders. The GO term enrichment analysis revealed a cluster of genes related to immune cell-related pathways (e.g., TMEM173, FADD, CD99) in the responder group, whereas the non-responder group had a high expression of genes related to nuclear replisome (POLD) and damaged DNA binding (ERCC2). Immunohistochemistry of these biomarkers showed that the expression levels of TMEM173 and FADD were significantly associated with the overall survival and progression-free survival of patients with recurrent GBM.

CONCLUSIONS

The candidate biomarkers identified in our protein analysis may be useful for predicting the clinical response to anti-angiogenic agents in patients with recurred GBM.

Microsatellite instability evaluation of patients with solid tumour: routine practice insight from a large series of Italian referral centre

DNA mismatch repair complex is involved in the maintenance of DNA stability. In the recent years, a plethora of technical approaches for microsatellite instability (MSI) analysis emerged. Here, we review the results of our MSI status evaluation by adopting a customised workflow on microfluidic system obtained in 4 years of diagnostic routine practice. Data from MSI status were retrieved from our institutional archive covering the period from January 2017 to December 2021. Microfluidic analysis was carried out on microfluidic platform. Results were inspected with a proprietary software. Overall, microsatellite stability (MSS) and MSI-high (MSI-H) profile was detected in n=423/458 (92.36%) and n=35/458 (7.64%) patients with metastatic CRC (mCRC), respectively. In addition, n=78/86 (90.70%) and n=8/86 (9.30%) patients without CRC showed an MSS and MSI-H profile. This review highlights the suitability of microfluidic approach in patients with cancer for MSI testing.

Comprehensive analysis of mutational signatures reveals distinct patterns and molecular processes across 27 pediatric cancers

Analysis of mutational signatures can reveal underlying molecular mechanisms of the processes that have imprinted the somatic mutations found in cancer genomes. Here, we analyze single base substitutions and small insertions and deletions in pediatric cancers encompassing 785 whole-genome sequenced tumors from 27 molecularly defined cancer subtypes. We identified only a small number of mutational signatures active in pediatric cancers, compared with previously analyzed adult cancers. Further, we report a significant difference in the proportion of pediatric tumors showing homologous recombination repair defect signatures compared with previous analyses. In pediatric leukemias, we identified an indel signature, not previously reported, characterized by long insertions in nonrepeat regions, affecting mainly intronic and intergenic regions, but also exons of known cancer genes. We provide a systematic overview of COSMIC v.3 mutational signatures active across pediatric cancers, which is highly relevant for understanding tumor biology and enabling future research in defining biomarkers of treatment response.

A Standardized Pathology Report for Gastric Cancer: 2nd Edition

The first edition of 'A Standardized Pathology Report for Gastric Cancer' was initiated by the Gastrointestinal Pathology Study Group of the Korean Society of Pathologists and published 17 years ago. Since then, significant advances have been made in the pathologic diagnosis, molecular genetics, and management of gastric cancer (GC). To reflect those changes, a committee for publishing a second edition of the report was formed within the Gastrointestinal Pathology Study Group of the Korean Society of Pathologists. This second edition consists of two parts: standard data elements and conditional data elements. The standard data elements contain the basic pathologic findings and items necessary to predict the prognosis of GC patients, and they are adequate for routine surgical pathology service. Other diagnostic and prognostic factors relevant to adjuvant therapy, including molecular biomarkers, are classified as conditional data elements to allow each pathologist to selectively choose items appropriate to the environment in their institution. We trust that the standardized pathology report will be helpful for GC diagnosis and facilitate large-scale multidisciplinary collaborative studies.

A standardized pathology report for gastric cancer: 2nd edition

The first edition of 'A Standardized Pathology Report for Gastric Cancer' was initiated by the Gastrointestinal Pathology Study Group of the Korean Society of Pathologists and published 17 years ago. Since then, significant advances have been made in the pathologic diagnosis, molecular genetics, and management of gastric cancer (GC). To reflect those changes, a committee for publishing a second edition of the report was formed within the Gastrointestinal Pathology Study Group of the Korean Society of Pathologists. This second edition consists of two parts: standard data elements and conditional data elements. The standard data elements contain the basic pathologic findings and items necessary to predict the prognosis of GC patients, and they are adequate for routine surgical pathology service. Other diagnostic and prognostic factors relevant to adjuvant therapy, including molecular biomarkers, are classified as conditional data elements to allow each pathologist to selectively choose items appropriate to the environment in their institution. We trust that the standardized pathology report will be helpful for GC diagnosis and facilitate large-scale multidisciplinary collaborative studies.

Identification of multiplicatively acting modulatory mutational signatures in cancer

BACKGROUND

A deep understanding of carcinogenesis at the DNA level underpins many advances in cancer prevention and treatment. Mutational signatures provide a breakthrough conceptualisation, as well as an analysis framework, that can be used to build such understanding. They capture somatic mutation patterns and at best identify their causes. Most studies in this context have focused on an inherently additive analysis, e.g. by non-negative matrix factorization, where the mutations within a cancer sample are explained by a linear combination of independent mutational signatures. However, other recent studies show that the mutational signatures exhibit non-additive interactions.

RESULTS

We carefully analysed such additive model fits from the PCAWG study cataloguing mutational signatures as well as their activities across thousands of cancers. Our analysis identified systematic and non-random structure of residuals that is left unexplained by the additive model. We used hierarchical clustering to identify cancer subsets with similar residual profiles to show that both systematic mutation count overestimation and underestimation take place. We propose an extension to the additive mutational signature model-multiplicatively acting modulatory processes-and develop a maximum-likelihood framework to identify such modulatory mutational signatures. The augmented model is expressive enough to almost fully remove the observed systematic residual patterns.

CONCLUSION

We suggest the modulatory processes biologically relate to sample specific DNA repair propensities with cancer or tissue type specific profiles. Overall, our results identify an interesting direction where to expand signature analysis.

Identifying tumor antigens and immuno-subtyping in colon adenocarcinoma to facilitate the development of mRNA vaccine

The mRNA vaccine has provided a promising approach for cancer immunotherapies. However, only a few mRNA vaccines have been developed against colon adenocarcinoma (COAD). Screening potential targets for mRNA vaccines from numerous candidates is a substantial challenge. Considering the tumor heterogeneity, only a subset of patients might respond to vaccinations. This study was conducted to identify potential candidates for mRNA vaccines, and distinguish appropriate subgroups of COAD patients for vaccination. A total of five tumor antigens with prognostic values were identified, including IGF2BP3, DPCR1, HOXD10, TRIM7, and ZIC5. The COAD patients were stratified into five immune subtypes (IS1-IS5), according to consensus clustering analysis. Higher tumor mutation burden (TMB) was observed in IS1 and IS5 subtypes. The IS1 and IS5 subtypes have shown the baseline of immune-hot tumor microenvironment, while other subtypes displayed immune desert phenotype. Distinct expressions of immune checkpoints (ICPs)-related genes and immunogenic cell death (ICD) modulators were observed among five immune subtypes. Finally, the immune landscape was conducted to narrow the immune components for better personalized mRNA-based vaccination. The IFIT3, PARP9, TAP1, STAT1, and OAS2 were confirmed as hub genes, and COAD patients with higher expressions of these genes might be more appropriate for mRNA vaccination. In conclusion, the IGF2BP3, DPCR1, HOXD10, TRIM7, and ZIC5 were identified as potential candidates for developing mRNA vaccines against COAD, and patients in IS1 and IS5 subtypes might respond better to mRNA vaccination.

Pressure-Induced Indirect-Direct Bandgap Transition of CsPbBr3 Single Crystal and Its Effect on Photoluminescence Quantum Yield

Despite extensive study, the bandgap characteristics of lead halide perovskites are not well understood. Usually, these materials are considered as direct bandgap semiconductors, while their photoluminescence quantum yield (PLQY) is very low in the solid state or single crystal (SC) state. Some researchers have noted a weak indirect bandgap below the direct bandgap transition in these perovskites. Herein, application of pressure to a CsPbBr3 SC and first-principles calculations reveal that the nature of the bandgap becomes more direct at a relatively low pressure due to decreased dynamic Rashba splitting. This effect results in a dramatic PLQY improvement, improved more than 90 times, which overturns the traditional concept that the PLQY of lead halide perovskite SC cannot exceed 10%. Application of higher pressure transformed the CsPbBr3 SC into a pure indirect bandgap phase, which can be maintained at near-ambient pressure. It is thus proved that lead halide perovskites can induce a phase transition between direct and indirect bandgaps. In addition, distinct piezochromism is observed for a perovskite SC for the first time. This work provides a novel framework to understand the optoelectronic properties of these important materials.

Mutational Signatures as Sensors of Environmental Exposures: Analysis of Smoking-Induced Lung Tissue Remodeling

Smoking is a widely recognized risk factor in the emergence of cancers and other lung diseases. Studies of non-cancer lung diseases typically investigate the role that smoking has in chronic changes in lungs that might predispose patients to the diseases, whereas most cancer studies focus on the mutagenic properties of smoking. Large-scale cancer analysis efforts have collected expression data from both tumor and control lung tissues, and studies have used control samples to estimate the impact of smoking on gene expression. However, such analyses may be confounded by tumor-related micro-environments as well as patient-specific exposure to smoking. Thus, in this paper, we explore the utilization of mutational signatures to study environment-induced changes of gene expression in control lung tissues from lung adenocarcinoma samples. We show that a joint computational analysis of mutational signatures derived from sequenced tumor samples, and the gene expression obtained from control samples, can shed light on the combined impact that smoking and tumor-related micro-environments have on gene expression and cell-type composition in non-neoplastic (control) lung tissue. The results obtained through such analysis are both supported by experimental studies, including studies utilizing single-cell technology, and also suggest additional novel insights. We argue that the study provides a proof of principle of the utility of mutational signatures to be used as sensors of environmental exposures not only in the context of the mutational landscape of cancer, but also as a reference for changes in non-cancer lung tissues. It also provides an example of how a database collected with the purpose of understanding cancer can provide valuable information for studies not directly related to the disease.

The mutational signatures of formalin fixation on the human genome

Clinical archives of patient material near-exclusively consist of formalin-fixed and paraffin-embedded (FFPE) blocks. The ability to precisely characterise mutational signatures from FFPE-derived DNA has tremendous translational potential. However, sequencing of DNA derived from FFPE material is known to be riddled with artefacts. Here we derive genome-wide mutational signatures caused by formalin fixation. We show that the FFPE-signature is highly similar to signature 30 (the signature of Base Excision Repair deficiency due to NTHL1 mutations), and chemical repair of DNA lesions leads to a signature highly similar to signature 1 (clock-like signature due to spontaneous deamination of methylcytosine). We demonstrate that using uncorrected mutational catalogues of FFPE samples leads to major mis-assignment of signature activities. To correct for this, we introduce FFPEsig, a computational algorithm to rectify the formalin-induced artefacts in the mutational catalogue. We demonstrate that FFPEsig enables accurate mutational signature analysis both in simulated and whole-genome sequenced FFPE cancer samples. FFPEsig thus provides an opportunity to unlock additional clinical potential of archival patient tissues.

Identification of a signature of evolutionarily conserved stress-induced mutagenesis in cancer

The clustering of mutations observed in cancer cells is reminiscent of the stress-induced mutagenesis (SIM) response in bacteria. Bacteria deploy SIM when faced with DNA double-strand breaks in the presence of conditions that elicit an SOS response. SIM employs DinB, the evolutionary precursor to human trans-lesion synthesis (TLS) error-prone polymerases, and results in mutations concentrated around DNA double-strand breaks with an abundance that decays with distance. We performed a quantitative study on single nucleotide variant calls for whole-genome sequencing data from 1950 tumors, non-inherited mutations from 129 normal samples, and acquired mutations in 3 cell line models of stress-induced adaptive mutation. We introduce statistical methods to identify mutational clusters, quantify their shapes and tease out the potential mechanism that produced them. Our results show that mutations in both normal and cancer samples are indeed clustered and have shapes indicative of SIM. Clusters in normal samples occur more often in the same genomic location across samples than in cancer suggesting loss of regulation over the mutational process during carcinogenesis. Additionally, the signatures of TLS contribute the most to mutational cluster formation in both patient samples as well as experimental models of SIM. Furthermore, a measure of cluster shape heterogeneity was associated with cancer patient survival with a hazard ratio of 5.744 (Cox Proportional Hazard Regression, 95% CI: 1.824-18.09). Our results support the conclusion that the ancient and evolutionary-conserved adaptive mutation response found in bacteria is a source of genomic instability in cancer. Biological adaptation through SIM might explain the ability of tumors to evolve in the face of strong selective pressures such as treatment and suggests that the conventional 'hit it hard' approaches to therapy could prove themselves counterproductive.

Higher ATM expression in lymphoblastoid cell lines from centenarian compared with younger women

With increased life expectancies in developed countries, cancer rates are becoming more common among the elderly. Cancer is typically driven by a combination of germline and somatic mutations accumulating during an individual's lifetime. Yet, many centenarians reach exceptionally old age without experiencing cancer. It was suggested that centenarians have more robust DNA repair and mitochondrial function, allowing improved maintenance of DNA stability. In this study, we applied real-time quantitative PCR to examine the expression of ATM in lymphoblastoid cell lines (LCLs) from 15 healthy female centenarians and 24 younger female donors aged 21-88 years. We observed higher ATM mRNA expression of in LCLs from female centenarians compared with both women aged 21-48 years (FD = 2.0, p = .0016) and women aged 56-88 years (FD = 1.8, p = .0094. Positive correlation was found between ATM mRNA expression and donors age (p = .0028). Levels of hsa-miR-181a-5p, which targets ATM, were lower in LCLs from centenarians compared with younger women. Our findings suggest a role for ATM in protection from age-related diseases, possibly reflecting more effective DNA repair, thereby reducing somatic mutation accumulation during aging. Further studies are required for analyzing additional DNA repair pathways in biosamples from centenarians and younger age men and women.

Downregulation of BLM RecQ helicase inhibits proliferation, promotes the apoptosis and enhances the sensitivity of bladder cancer cells to cisplatin

Bloom syndrome protein (BLM) is known to maintain genomic integrity including DNA repair, recombination, replication and transcription. Its dysregulation affects the genomic instability of cells, which results in a high risk of developing various types of cancer and even Bloom syndrome. However, to date, to the best of our knowledge, no association has been made between human BLM and bladder cancer. Thus, the aim of the present study was to investigate the role of BLM in human bladder cancer. The expression pattern of BLM in bladder cancer tissue was detected by immunohistochemistry. The viability, proliferation, cell cycle and apoptosis of bladder cancer cell lines were determined by Cell Counting Kit-8, EdU and flow cytometry following transfection of BLM small interfering RNA. Finally, the effect of BLM on sensitivity of bladder cancer cell lines to cisplatin was investigated by reverse transcription-quantitative PCR and western blot. It was demonstrated that the expression of BLM in human bladder cancer was increased compared with adjacent healthy bladder tissues. In addition, silencing of BLM inhibited the proliferation and promoted the apoptosis of bladder cancer cells and it also enhanced the sensitivity of bladder cancer cells to cisplatin. Together, the findings of the present study demonstrated that the regulation of BLM activity may have potential for use as a novel therapeutic target and a predictor for the prognosis of bladder cancer.

New Potential Immune Biomarkers in the Era of Precision Medicine: Lights and Shadows in Colorectal Cancer

Genetic alterations in CRC have shown a negative predictive and prognostic role in specific target therapies. The onset of immunotherapy has also undergone remarkable therapeutic innovation, although limited to a small subgroup of patients, the MSI-H/dMMR, which represents only 5% of CRC. Research is moving forward to identify whether other biomarkers can predict response to ICIs, despite various limitations regarding expression and identification methods. For this purpose, TMB, LAG3, and PD-L1 expression have been retrospectively evaluated in several solid tumors establishing the rationale to design clinical trials with concurrent inhibition of LAG3 and PD-1 results in a significant advantage in PFS and OS in advanced melanoma patients. Based on these data, there are clinical trials ongoing in the CRC as well. This review aims to highlight what is already known about genetic mutations and genomic alterations in CRC, their inhibition with targeted therapies and immune checkpoints inhibitors, and new findings useful to future treatment strategies.

Pan-Cancer Analysis for Immune Cell Infiltration and Mutational Signatures Using Non-Negative Canonical Correlation Analysis

Mutational signatures indicate the mutational processes and substitution patterns in cancer cell genomes. However, the functional consequences of mutational signatures remain unclear, and there have been no comprehensive systematic studies to examine the relationships between the mutational signatures and the immune cell infiltration. Here, the relationship between mutational signatures and immune cell infiltration using non-negative canonical correlation analysis based on 8927 patients across 25 tumor types was investigated. By inspecting mutational signatures with the maximal coefficients determined by the non-negative canonical correlation analysis, the study identified mutational signatures related to immune cell infiltration composed of tumor microenvironments. The analysis was validated by showing that the genes associated with the identified mutational signatures were linked to overall survival by a Kaplan–Meier curve and a log-rank test and were mainly related to immunity by gene set enrichment analysis. These results will help expand our knowledge of tumor biology and recognize the functional roles and associations of immune systems with mutational signatures.

Estimating tumor mutational burden from RNA-sequencing without a matched-normal sample

Detection of somatic mutations using patients sequencing data has many clinical applications, including the identification of cancer driver genes, detection of mutational signatures, and estimation of tumor mutational burden (TMB). We have previously developed a tool for detection of somatic mutations using tumor RNA and a matched-normal DNA. Here, we further extend it to detect somatic mutations from RNA sequencing data without a matched-normal sample. This is accomplished via a machine-learning approach that classifies mutations as either somatic or germline based on various features. When applied to RNA-sequencing of >450 melanoma samples high precision and recall are achieved, and both mutational signatures and driver genes are correctly identified. Finally, we show that RNA-based TMB is significantly associated with patient survival, showing similar or higher significance level as compared to DNA-based TMB. Our pipeline can be utilized in many future applications, analyzing novel and existing datasets where only RNA is available.

Health Care Resource Utilization and Costs Associated with Disease Progression in Ovarian Cancer

Introduction

Ovarian cancer (OC) is one of the leading causes of cancer mortality among women in the United States. With the approval of first-line maintenance therapies, patients with OC experienced prolonged first-line progression-free survival. While the literature addresses some costs associated with OC, further research is needed on the costs of progression that are potentially deferred or prevented by early maintenance. The objective of this study was to capture the health care resource utilization and costs of patients with advanced OC who never received poly(ADP ribose) polymerase (PARP) inhibitor maintenance.

Methods

We conducted a descriptive retrospective analysis of treatment patterns and the consequences of progression through several lines of therapy (LOTs) in patients with OC, using claims from commercial and Medicare Advantage health plan members in the United States from the Optum Research Database between January 1, 2010, and April 30, 2019. Patients were required to have an index OC diagnosis (≥ 2 non-diagnostic claims). We examined up to 4 LOTs and the time between treatments.

Results

A total of 5498 women met the eligibility criteria. As the number of LOTs increased, the median duration of each line decreased from 137 days in LOT1 to 94 days in LOT4, and the time between lines also decreased from 245 to 0 days. Ambulatory care visits were a major driver of health care resource utilization, with a median of about 6 monthly visits during active treatment. The mean total monthly health care costs for patients with at least 2 LOTs were US$8588 (SD: $8533) before LOT2 and increased to $15,358 (SD: $21,460) during or after LOT2.

Conclusions

Prolonging progression-free survival after first-line treatment in patients with OC may provide the opportunity to delay or prevent later treatment, the financial toxicity felt by patients, and the economic burden to the health care system associated with progression.

Ovarian cancer is a complex disease in which > 70% of patients are diagnosed with advanced disease, and one of the leading causes of cancer mortality among women in the United States. A variety of maintenance therapy options, including bevacizumab, PARP inhibitors, and PARP plus bevacizumab combination therapies, have demonstrated improvements in progression-free survival. By delaying disease progression after completion of first-line therapy, a simultaneous decrease in post-progression health care costs may be seen. The objective of this study was to capture the health care resource utilization and costs of patients with advanced ovarian cancer who did not receive a PARP inhibitor at any time in their treatment

In patients never receiving a PARP inhibitor, this study documented substantial health care resource usage and costs associated with progression beyond the first line of treatment (surgery and/or chemotherapy) in ovarian cancer. These were largely driven by the number of ambulatory care visits. When these visits are combined with emergency department visits and inpatient stays, high costs are incurred by both patients and third-party payers

Prolonging progression-free survival after first-line treatment in patients with ovarian cancer may delay or prevent the need for later treatment, the financial burden felt by patients, and the economic burden to the health care system associated with subsequent disease progressions

Mutational signatures and processes in hepatobiliary cancers

The evolutionary history of hepatobiliary cancers is embedded in their genomes. By analysing their catalogue of somatic mutations and the DNA sequence context in which they occur, it is possible to infer the mechanisms underpinning tumorigenesis. These mutational signatures reflect the exogenous and endogenous origins of genetic damage as well as the capacity of hepatobiliary cells to repair and replicate DNA. Genomic analysis of thousands of patients with hepatobiliary cancers has highlighted the diversity of mutagenic processes active in these malignancies, highlighting a prominent source of the inter-cancer-type, inter-patient, intertumour and intratumoural heterogeneity that is observed clinically. However, a substantial proportion of mutational signatures detected in hepatocellular carcinoma and biliary tract cancer remain of unknown cause, emphasizing the important contribution of processes yet to be identified. Exploiting mutational signatures to retrospectively understand hepatobiliary carcinogenesis could advance preventative management of these aggressive tumours as well as potentially predict treatment response and guide the development of therapies targeting tumour evolution.