Whole genome and transcriptome analysis enhances precision cancer treatment options

A review on trends in development and translation of omics signatures in cancer

The field of cancer genomics and transcriptomics has evolved from targeted profiling to swift sequencing of individual tumor genome and transcriptome. The steady growth in genome, epigenome, and transcriptome datasets on a genome-wide scale has significantly increased our capability in capturing signatures that represent both the intrinsic and extrinsic biological features of tumors. These biological differences can help in precise molecular subtyping of cancer, predicting tumor progression, metastatic potential, and resistance to therapeutic agents. In this review, we summarized the current development of genomic, methylomic, transcriptomic, proteomic and metabolic signatures in the field of cancer research and highlighted their potentials in clinical applications to improve diagnosis, prognosis, and treatment decision in cancer patients.

Development of automated proteomic workflows utilizing silicon-based coupling agents

Automated methods for enzyme immobilization via 4-triethoxysilylbutyraldehyde (TESB) derived silicone-based coupling agents were developed. TESB and its oxidized derivative, 4-triethoxysilylbutanoic acid (TESBA), were determined to be the most effective. The resulting immobilized enzyme particles (IEPs) displayed robustness, rapid digestion, and immobilization efficiency of 51 ± 8%. Furthermore, we automated the IEP procedure, allowing for multiple enzymes, and/or coupling agents to be fabricated at once, in a fraction of the time via an Agilent Bravo. The automated trypsin TESB and TESBA IEPs were shown to rival a classical in-gel digestion method. Moreover, pepsin IEPs favored cleavage at leucine (>50%) over aromatic and methionine residues. The IEP method was then adapted for an in-situ immobilized enzyme microreactor (IMER) fabrication. We determined that TESBA could functionalize the silica capillary's inner wall while simultaneously acting as an enzyme coupler. The IMER digestion of bovine serum albumin (BSA), mirroring IEP digestion conditions, yielded a 33-40% primary sequence coverage per LC-MS/MS analysis in as little as 15 min. Overall, our findings underscore the potential of both IEP and IMER methods, paving the way for automated analysis and a reduction in enzyme waste through reuse, thereby contributing to a more cost-effective and timely study of the proteome. SIGNIFICANCE: This research introduces 4-triethoxysilylbutyraldehyde (TESB) and its derivatives as silicon-based enzyme coupling agents and an automated liquid handling method for bottom-up proteomics (BUP) while streamlining sample preparation for high-throughput processing. Additionally, immobilized enzyme particle (IEP) fabrication and digestion within the 96-well plate allows for flexibility in protocol where different enzyme-coupler combinations can be employed simultaneously. By enabling the digestion of entire microplates and reducing manual labor, the proposed method enhances reproducibility and offers a more efficient alternative to classical in-gel techniques. Furthermore, pepsin IEPs were noted to favor cleavage at leucine residues which represents an interesting finding when compared to the literature that warrants further study. The capability of immobilized enzyme microreactors (IMER) for rapid digestion (in as little as 15 min) demonstrated the system's efficiency and potential for rapid proteomic analysis. This advancement in BUP not only improves efficiency, but also opens avenues for a fully automated, mass spectrometry-integrated proteomics workflow, promising to expedite research and discoveries in complex biological studies.

Comprehensive Genomic Profiling Alters Clinical Diagnoses in a Significant Fraction of Tumors Suspicious of Sarcoma

PURPOSE

Tumor classification is a key component in personalized cancer care. For soft-tissue and bone tumors, this classification is currently based primarily on morphology assessment and IHC staining. However, these standard-of-care methods can pose challenges for pathologists. We therefore assessed how whole-genome and whole-transcriptome sequencing (WGTS) impacted tumor classification and clinical management when interpreted together with histomorphology.

EXPERIMENTAL DESIGN

We prospectively evaluated WGTS in routine diagnostics of 200 soft-tissue and bone tumors suspicious for malignancy, including DNA and RNA isolation from the tumor, and DNA isolation from a peripheral blood sample or any non-tumor tissue.

RESULTS

On the basis of specific genomic alterations or absence of presumed findings, WGTS resulted in reclassification of 7% (13/197) of the histopathologic diagnoses. Four cases were downgraded from low-grade sarcomas to benign lesions, and two cases were reclassified as metastatic malignant melanomas. Fusion genes associated with specific tumor entities were found in 30 samples. For malignant soft-tissue and bone tumors, we identified treatment relevant variants in 15% of cases. Germline pathogenic variants associated with a hereditary cancer syndrome were found in 22 participants (11%).

CONCLUSIONS

WGTS provides an important dimension of data that aids in the classification of soft-tissue and bone tumors, correcting a significant fraction of clinical diagnoses, and identifies molecular targets relevant for precision medicine. However, genetic findings need to be evaluated in their morphopathologic context, just as germline findings need to be evaluated in the context of patient phenotype and family history.

Molecular subtypes of neuroendocrine carcinomas: A cross-tissue classification framework based on five transcriptional regulators

Neuroendocrine carcinomas (NECs) are extremely lethal malignancies that can arise at almost any anatomic site. Characterization of NECs is hindered by their rarity and significant inter- and intra-tissue heterogeneity. Herein, through an integrative analysis of over 1,000 NECs originating from 31 various tissues, we reveal their tissue-independent convergence and further unveil molecular divergence driven by distinct transcriptional regulators. Pan-tissue NECs are therefore categorized into five intrinsic subtypes defined by ASCL1, NEUROD1, HNF4A, POU2F3, and YAP1. A comprehensive portrait of these subtypes is depicted, highlighting subtype-specific transcriptional programs, genomic alterations, evolution trajectories, therapeutic vulnerabilities, and clinicopathological presentations. Notably, the newly discovered HNF4A-dominated subtype-H exhibits a gastrointestinal-like signature, wild-type RB1, unique neuroendocrine differentiation, poor chemotherapeutic response, and prevalent large-cell morphology. The proposal of uniform classification paradigm illuminates transcriptional basis of NEC heterogeneity and bridges the gap across different lineages and cytomorphological variants, in which context-dependent prevalence of subtypes underlies their phenotypic disparities.

Effectiveness of G-CSF in chemotherapy for digestive system tumors: a systematic review of the Clinical Practice Guidelines for the Use of G-CSF 2022 delineated by the Japan Society of Clinical Oncology

BACKGROUND

Granulocyte colony-stimulating factor (G-CSF) reportedly reduces the risk of neutropenia and subsequent infections caused by cancer chemotherapy. Although several guidelines recommend using G-CSF in primary prophylaxis according to the incidence rate of chemotherapy-induced febrile neutropenia (FN), the effectiveness of G-CSF in digestive system tumor chemotherapy remains unclear. To address these clinical questions, we conducted a systematic review as part of revising the Clinical Practice Guidelines for the Use of G-CSF 2022 published by the Japan Society of Clinical Oncology.

METHODS

This systematic review addressed two main clinical questions (CQ): CQ1: "Is primary prophylaxis with G-CSF effective in chemotherapy?", and CQ2: "Is increasing the intensity of chemotherapy with G-CSF effective?" We reviewed different types of digestive system tumors, including esophageal, gastric, pancreatic, biliary tract, colorectal, and neuroendocrine carcinomas. PubMed, Cochrane Library, and Ichushi-Web databases were searched for information sources. Independent systematic reviewers conducted two rounds of screening and selected relevant records for each CQ. Finally, the working group members synthesized the strength of evidence and recommendations.

RESULTS

After two rounds of screening, 5/0/3/0/2/0 records were extracted for CQ1 of esophageal/gastric/pancreatic/biliary tract/colorectal/ and neuroendocrine carcinoma, respectively. Additionally, a total of 2/6/1 records were extracted for CQ2 of esophageal/pancreatic/colorectal cancer, respectively. The strength of evidence and recommendations were evaluated for CQ1 of colorectal cancer; however, we could not synthesize recommendations for other CQs owing to the lack of records.

CONCLUSION

The use of G-CSF for primary prophylaxis in chemotherapy for colorectal cancer is inappropriate.

Rapid microdissection of tissue sections via laser ablation

We demonstrate a method for tissue microdissection using scanning laser ablation that is approximately two orders of magnitude faster than conventional laser capture microdissection. Our novel approach uses scanning laser optics and a slide coating under the tissue that can be excited by the laser to selectively eject regions of tissue for further processing. Tissue was dissected at 0.117 s/mm2 without reduction in yield, sequencing insert size or base quality compared with undissected tissue. From eight cases, 58-416 mm2 of tissue was obtained from one to four slides in 7-48 seconds total dissection time per case. These samples underwent exome sequencing and we found the variant allelic fraction increased in regions enriched for tumour as expected. This suggests that our ablation technique may be useful as a tool in both clinical and research labs.

Whole genome and transcriptome integrated analyses guide clinical care of pediatric poor prognosis cancers

The role for routine whole genome and transcriptome analysis (WGTA) for poor prognosis pediatric cancers remains undetermined. Here, we characterize somatic mutations, structural rearrangements, copy number variants, gene expression, immuno-profiles and germline cancer predisposition variants in children and adolescents with relapsed, refractory or poor prognosis malignancies who underwent somatic WGTA and matched germline sequencing. Seventy-nine participants with a median age at enrollment of 8.8 y (range 6 months to 21.2 y) are included. Germline pathogenic/likely pathogenic variants are identified in 12% of participants, of which 60% were not known prior. Therapeutically actionable variants are identified by targeted gene report and whole genome in 32% and 62% of participants, respectively, and increase to 96% after integrating transcriptome analyses. Thirty-two molecularly informed therapies are pursued in 28 participants with 54% achieving a clinical benefit rate; objective response or stable disease ≥6 months. Integrated WGTA identifies therapeutically actionable variants in almost all tumors and are directly translatable to clinical care of children with poor prognosis cancers.

An integrated analysis revealing the angiogenic function of TP53I11 in tumor microenvironment

Despite growing evidence suggesting an important contribution of Tumor Protein P53 Inducible Protein 11 (TP53I11) in cancer progression, the role of TP53I11 remains unclear. Our first pan-cancer analysis of TP53I11 showed some tumor tissues displayed reduced TP53I11 expression compared to normal tissues, while others exhibited high TP53I11 expression. Meanwhile, TP53I11 expression carries a particular pan-cancer risk, as high TP53I11 expression levels are detrimental to survival for BRCA, KIRP, MESO, and UVM, but to beneficial survival for KIRC. We demonstrated that TP53I11 expression negatively correlates with DNA methylation in most cancers, and the S14 residue of TP53I11 is phosphorylated in several cancer types. Additionally, TP53I11 was found to be associated with endothelial cells in pan-cancer, and functional enrichment analysis provided strong evidence for its role in tumor angiogenesis. In vitro angiogenesis assays confirmed that TP53I11 can promote angiogenic function of human umbilical vein endothelial cells (HUVECs) in vitro. Mechanistic investigations reveal that TP53I11 is transcriptionally up-regulated by HIF2A under hypoxia.

Accelerating Drug Development Using Spatial Multi-omics

SUMMARY

Spatial biology approaches enabled by innovations in imaging biomarker platforms and artificial intelligence-enabled data integration and analysis provide an assessment of patient and disease heterogeneity at ever-increasing resolution. The utility of spatial biology data in accelerating drug programs, however, requires balancing exploratory discovery investigations against scalable and clinically applicable spatial biomarker analysis.

Multiomic-Based Molecular Landscape of FaDu Xenograft Tumors in Mice after a Combinatorial Treatment with Radiation and an HSP90 Inhibitor Identifies Adaptation-Induced Targets of Resistance and Therapeutic Intervention

Treatments involving radiation and chemotherapy alone or in combination have improved patient survival and quality of life. However, cancers frequently evade these therapies due to adaptation and tumor evolution. Given the complexity of predicting response based solely on the initial genetic profile of a patient, a predetermined treatment course may miss critical adaptation that can cause resistance or induce new targets for drug and immunotherapy. To address the timescale for these evasive mechanisms, using a mouse xenograft tumor model, we investigated the rapidity of gene expression (mRNA), molecular pathway, and phosphoproteome changes after radiation, an HSP90 inhibitor, or combination. Animals received radiation, drug, or combination treatment for 1 or 2 weeks and were then euthanized along with a time-matched untreated group for comparison. Changes in gene expression occur as early as 1 week after treatment initiation. Apoptosis and cell death pathways were activated in irradiated tumor samples. For the HSP90 inhibitor and combination treatment at weeks 1 and 2 compared with Control Day 1, gene-expression changes induced inhibition of pathways including invasion of cells, vasculogenesis, and viral infection among others. The combination group included both drug-alone and radiation-alone changes. Our data demonstrate the rapidity of gene expression and functional pathway changes in the evolving tumor as it responds to treatment. Discovering these phenotypic adaptations may help elucidate the challenges in using sustained treatment regimens and could also define evolving targets for therapeutic efficacy.

Added value of whole-exome and RNA sequencing in advanced and refractory cancer patients with no molecular-based treatment recommendation based on a 90-gene panel

INTRODUCTION

The objective was to determine the added value of comprehensive molecular profile by whole-exome and RNA sequencing (WES/RNA-Seq) in advanced and refractory cancer patients who had no molecular-based treatment recommendation (MBTR) based on a more limited targeted gene panel (TGP) plus array-based comparative genomic hybridization (aCGH).

MATERIALS AND METHODS

In this retrospective analysis, we selected 50 patients previously included in the PROFILER trial (NCT01774409) for which no MBT could be recommended based on a targeted 90-gene panel and aCGH. For each patient, the frozen tumor sample mirroring the FFPE sample used for TGP/aCGH analysis were processed for WES and RNA-Seq. Data from TGP/aCGH were reanalyzed, and together with WES/RNA-Seq, findings were simultaneously discussed at a new molecular tumor board (MTB).

RESULTS

After exclusion of variants of unknown significance, a total of 167 somatic molecular alterations were identified in 50 patients (median: 3 [1-10]). Out of these 167 relevant molecular alterations, 51 (31%) were common to both TGP/aCGH and WES/RNA-Seq, 19 (11%) were identified by the TGP/aCGH only and 97 (58%) were identified by WES/RNA-Seq only, including two fusion transcripts in two patients. A MBTR was provided in 4/50 (8%) patients using the information from TGP/aCGH versus 9/50 (18%) patients using WES/RNA-Seq findings. Three patients had similar recommendations based on TGP/aCGH and WES/RNA-Seq.

CONCLUSIONS

In advanced and refractory cancer patients in whom no MBTR was recommended from TGP/aCGH, WES/RNA-Seq allowed to identify more alterations which may in turn, in a limited fraction of patients, lead to new MBTR.

New clinical trial design in precision medicine: discovery, development and direction

In the era of precision medicine, it has been increasingly recognized that individuals with a certain disease are complex and different from each other. Due to the underestimation of the significant heterogeneity across participants in traditional "one-size-fits-all" trials, patient-centered trials that could provide optimal therapy customization to individuals with specific biomarkers were developed including the basket, umbrella, and platform trial designs under the master protocol framework. In recent years, the successive FDA approval of indications based on biomarker-guided master protocol designs has demonstrated that these new clinical trials are ushering in tremendous opportunities. Despite the rapid increase in the number of basket, umbrella, and platform trials, the current clinical and research understanding of these new trial designs, as compared with traditional trial designs, remains limited. The majority of the research focuses on methodologies, and there is a lack of in-depth insight concerning the underlying biological logic of these new clinical trial designs. Therefore, we provide this comprehensive review of the discovery and development of basket, umbrella, and platform trials and their underlying logic from the perspective of precision medicine. Meanwhile, we discuss future directions on the potential development of these new clinical design in view of the "Precision Pro", "Dynamic Precision", and "Intelligent Precision". This review would assist trial-related researchers to enhance the innovation and feasibility of clinical trial designs by expounding the underlying logic, which be essential to accelerate the progression of precision medicine.

Integrative score based on CDK6, PD-L1 and TMB predicts response to platinum-based chemotherapy and PD-1/PD-L1 blockade in muscle-invasive bladder cancer

BACKGROUND

Cyclin-dependent kinase 6 (CDK6) was proved to be an important regulator in the progression of cell cycle and has been a promising therapeutic target in cancer treatment. However, the clinical significance of CDK6 in muscle-invasive bladder cancer (MIBC) remains obscure. Herein, we attempt to explore the clinical relevance of CDK6 and assess the feasibility of the integrative model to predict immune checkpoint blockade (ICB) response.

METHODS

This study enrolled 933 patients with muscle-invasive bladder cancer (MIBC) from Zhongshan Hospital (ZSHS), The Cancer Genome Atlas (TCGA), Chemo, IMvigor210 and UC-GENOME cohorts. Kaplan-Meier survival and Cox regression analyses were performed to assess clinical outcomes based on CDK6 expression.

RESULTS

High CDK6 expression conferred poor prognosis and superior response to platinum-based chemotherapy but inferior response to ICB in MIBC. Furthermore, the integrative model named response score based on CDK6, PD-L1 and TMB could better predict the response to ICB and chemotherapy. Patients with higher response scores were characterised by inflamed immune microenvironment and genomic instability.

CONCLUSIONS

CDK6 expression was correlated with prognosis and therapy response in MIBC. Integration of CDK6, PD-L1 and TMB could better identify patients who were most likely to benefit from ICB and chemotherapy.

Molecular portraits of patients with intrahepatic cholangiocarcinoma who diverge as rapid progressors or long survivors on chemotherapy

OBJECTIVE

Cytotoxic agents are the cornerstone of treatment for patients with advanced intrahepatic cholangiocarcinoma (iCCA), despite heterogeneous benefit. We hypothesised that the pretreatment molecular profiles of diagnostic biopsies can predict patient benefit from chemotherapy and define molecular bases of innate chemoresistance.

DESIGN

We identified a cohort of advanced iCCA patients with comparable baseline characteristics who diverged as extreme outliers on chemotherapy (survival <6 m in rapid progressors, RP; survival >23 m in long survivors, LS). Diagnostic biopsies were characterised by digital pathology, then subjected to whole-transcriptome profiling of bulk and geospatially macrodissected tissue regions. Spatial transcriptomics of tumour-infiltrating myeloid cells was performed using targeted digital spatial profiling (GeoMx). Transcriptome signatures were evaluated in multiple cohorts of resected cancers. Signatures were also characterised using in vitro cell lines, in vivo mouse models and single cell RNA-sequencing data.

RESULTS

Pretreatment transcriptome profiles differentiated patients who would become RPs or LSs on chemotherapy. Biologically, this signature originated from altered tumour-myeloid dynamics, implicating tumour-induced immune tolerogenicity with poor response to chemotherapy. The central role of the liver microenviroment was confrmed by the association of the RPLS transcriptome signature with clinical outcome in iCCA but not extrahepatic CCA, and in liver metastasis from colorectal cancer, but not in the matched primary bowel tumours.

CONCLUSIONS

The RPLS signature could be a novel metric of chemotherapy outcome in iCCA. Further development and validation of this transcriptomic signature is warranted to develop precision chemotherapy strategies in these settings.

Tumor Copy Number Alteration Burden as a Predictor for Resistance to Immune Checkpoint Blockade across Different Cancer Types

Immune checkpoint blockade (ICB) benefits only a subset of advanced cancer patients, and predictive biomarkers for immunotherapy response are needed. Recently, copy number alteration (CNA) burden has been proposed to predict ICB resistance. We assessed this finding using the publicly accessible data for 1661 ICB-treated patients whose tumors were profiled by MSK-IMPACT, an approved targeted assay in clinical care. We tested the hypothesis that the continuous increase in CNA burden is associated with poor overall survival following ICB. In addition, we hypothesized that the combinatorial biomarkers of tumor mutational burden (TMB) and CNA burden would better stratify patients for immune status and ICB response. Of the 1661 cases, 79% (n = 1307) were treated with anti PD-1/PD-L1 and the remaining 21% (n = 354) with anti CTLA-4 or the combination of both. In a multivariate analysis, increase in CNA burden was associated with poor overall survival [HR = 1.52, 95% CI (1.01-2.30), p = 0.04]. The combination of biomarkers TMB and CNA burden stratified patients into four clinically distinct subsets among which "LowTMB/HighCNA" showed the worst survival (p < 0.0001). The four patient subsets had unique CNA profiles and enriched pathways, which could predict transcriptional and phenotypic effects related to immune signaling and CD8+ T-cell abundance in the tumor microenvironment. CNA burden was associated with poor overall survival in patients receiving ICB and could improve patient stratification when incorporated with TMB. These findings may guide patient selection for immunotherapy or alternative strategies.

Whole genome sequencing in clinical practice

Whole genome sequencing (WGS) is becoming the preferred method for molecular genetic diagnosis of rare and unknown diseases and for identification of actionable cancer drivers. Compared to other molecular genetic methods, WGS captures most genomic variation and eliminates the need for sequential genetic testing. Whereas, the laboratory requirements are similar to conventional molecular genetics, the amount of data is large and WGS requires a comprehensive computational and storage infrastructure in order to facilitate data processing within a clinically relevant timeframe. The output of a single WGS analyses is roughly 5 MIO variants and data interpretation involves specialized staff collaborating with the clinical specialists in order to provide standard of care reports. Although the field is continuously refining the standards for variant classification, there are still unresolved issues associated with the clinical application. The review provides an overview of WGS in clinical practice - describing the technology and current applications as well as challenges connected with data processing, interpretation and clinical reporting.

Circulating tumor DNA (ctDNA) as a biomarker for lung cancer: Early detection, monitoring and therapy prediction

Circulating tumor DNA (ctDNA), i.e., DNA shed from tumor cells into the bloodstream, is emerging as one of the most useful plasma biomarkers in patients with multiple types of cancer, including patients with non-small cell lung cancer (NSCLC). Indeed, NSCLC was the first malignancy in which measurement of ctDNA was approved for clinical use, i.e., mutational testing of EGFR for predicting response to EGFR tyrosine kinase inhibitors in patients with advanced disease. Although historically the gold standard method for EGFR mutational analysis required tumor tissue, the use of ctDNA is more convenient and safer for patients, results in a faster turn-around-time for return of results, provides a more complete representation of genetic alteration in heterogeneous tumors and is less costly to perform. Emerging uses of ctDNA in patients with lung or suspected lung cancer include screening for early disease, surveillance following initial treatment and monitoring response to therapy in metastatic disease. For evaluating therapy response, ctDNA appears to be especially useful in patients receiving targeted therapies against driver oncogenes or immunotherapy. Further work should not only validate these emerging findings but also aim to optimize and standardize ctDNA assays.

HRD related signature 3 predicts clinical outcome in advanced tubo-ovarian high-grade serous carcinoma

OBJECTIVES

We evaluated usability of single base substitution signature 3 (Sig3) as a biomarker for homologous recombination deficiency (HRD) in tubo-ovarian high-grade serous carcinoma (HGSC).

MATERIALS AND METHODS

This prospective observational trial includes 165 patients with advanced HGSC. Fresh tissue samples (n = 456) from multiple intra-abdominal areas at diagnosis and after neoadjuvant chemotherapy (NACT) were collected for whole-genome sequencing. Sig3 was assessed by fitting samples independently with COSMIC v3.2 reference signatures. An HR scar assay was applied for comparison. Progression-free survival (PFS) and overall survival (OS) were studied using Kaplan-Meier and Cox regression analysis.

RESULTS

Sig3 has a bimodal distribution, eliminating the need for an arbitrary cutoff typical in HR scar tests. Sig3 could be assessed from samples with low (10%) cancer cell proportion and was consistent between multiple samples and stable during NACT. At diagnosis, 74 (45%) patients were HRD (Sig3+), while 91 (55%) were HR proficient (HRP, Sig3-). Sig3+ patients had longer PFS and OS than Sig3- patients (22 vs. 13 months and 51 vs. 34 months respectively, both p < 0.001). Sig3 successfully distinguished the poor prognostic HRP group among BRCAwt patients (PFS 19 months for Sig3+ and 13 months for Sig3- patients, p < 0.001). However, Sig3 at diagnosis did not predict chemoresponse anymore in the first relapse. The patient-level concordance between Sig3 and HR scar assay was 87%, and patients with HRD according to both tests had the longest median PFS.

CONCLUSIONS

Sig3 is a prognostic marker in advanced HGSC and useful tool in patient stratification for HRD.

Insights for precision oncology from the integration of genomic and clinical data of 13,880 tumors from the 100,000 Genomes Cancer Programme

The Cancer Programme of the 100,000 Genomes Project was an initiative to provide whole-genome sequencing (WGS) for patients with cancer, evaluating opportunities for precision cancer care within the UK National Healthcare System (NHS). Genomics England, alongside NHS England, analyzed WGS data from 13,880 solid tumors spanning 33 cancer types, integrating genomic data with real-world treatment and outcome data, within a secure Research Environment. Incidence of somatic mutations in genes recommended for standard-of-care testing varied across cancer types. For instance, in glioblastoma multiforme, small variants were present in 94% of cases and copy number aberrations in at least one gene in 58% of cases, while sarcoma demonstrated the highest occurrence of actionable structural variants (13%). Homologous recombination deficiency was identified in 40% of high-grade serous ovarian cancer cases with 30% linked to pathogenic germline variants, highlighting the value of combined somatic and germline analysis. The linkage of WGS and longitudinal life course clinical data allowed the assessment of treatment outcomes for patients stratified according to pangenomic markers. Our findings demonstrate the utility of linking genomic and real-world clinical data to enable survival analysis to identify cancer genes that affect prognosis and advance our understanding of how cancer genomics impacts patient outcomes.

Enriching single-arm clinical trials with external controls: possibilities and pitfalls

For the past decade, it has become commonplace to provide rapid answers and early patient access to innovative treatments in the absence of randomized clinical trials (RCT), with benefits estimated from single-arm trials. This trend is important in oncology, notably when assessing new targeted therapies. Some of those uncontrolled trials further include an external/synthetic control group as an innovative way to provide an indirect comparison with a pertinent control group. We aimed to provide some guidelines as a comprehensive tool for (1) the critical appraisal of those comparisons or (2) for performing a single-arm trial. We used the example of ciltacabtagene autoleucel for the treatment of adult patients with relapsed or refractory multiple myeloma after 3 or more treatment lines as an illustrative example. We propose a 3-step guidance. The first step includes the definition of an estimand, which encompasses the treatment effect and the targeted population (whole population or restricted to single-arm trial or external controls), reflecting a clinical question. The second step relies on the adequate selection of external controls from previous RCTs or real-world data from patient cohorts, registries, or electronic patient files. The third step consists of choosing the statistical approach targeting the treatment effect defined above and depends on the available data (individual-level data or aggregated external data). The validity of the treatment effect derived from indirect comparisons heavily depends on careful methodological considerations included in the proposed 3-step procedure. Because the level of evidence of a well-conducted RCT cannot be guaranteed, the evaluation is more important than in standard settings.

Antibody-Drug Conjugates in Solid Tumor Oncology: An Effectiveness Payday with a Targeted Payload

Antibody-drug conjugates (ADCs) are at the forefront of the drug development revolution occurring in oncology. Formed from three main components-an antibody, a linker molecule, and a cytotoxic agent ("payload"), ADCs have the unique ability to deliver cytotoxic agents to cells expressing a specific antigen, a great leap forward from traditional chemotherapeutic approaches that cause widespread effects without specificity. A variety of payloads can be used, including most frequently microtubular inhibitors (auristatins and maytansinoids), as well as topoisomerase inhibitors and alkylating agents. Finally, linkers play a critical role in the ADCs' effect, as cleavable moieties that serve as linkers impact site-specific activation as well as bystander killing effects, an upshot that is especially important in solid tumors that often express a variety of antigens. While ADCs were initially used in hematologic malignancies, their utility has been demonstrated in multiple solid tumor malignancies, including breast, gastrointestinal, lung, cervical, ovarian, and urothelial cancers. Currently, six ADCs are FDA-approved for the treatment of solid tumors: ado-trastuzumab emtansine and trastuzumab deruxtecan, both anti-HER2; enfortumab-vedotin, targeting nectin-4; sacituzuzmab govitecan, targeting Trop2; tisotumab vedotin, targeting tissue factor; and mirvetuximab soravtansine, targeting folate receptor-alpha. Although they demonstrate utility and tolerable safety profiles, ADCs may become ineffective as tumor cells undergo evolution to avoid expressing the specific antigen being targeted. Furthermore, the current cost of ADCs can be limiting their reach. Here, we review the structure and functions of ADCs, as well as ongoing clinical investigations into novel ADCs and their potential as treatments of solid malignancies.

Genetic matching for time-dependent treatments: a longitudinal extension and simulation study

BACKGROUND

Longitudinal matching can mitigate confounding in observational, real-world studies of time-dependent treatments. To date, these methods have required iterative, manual re-specifications to achieve covariate balance. We propose a longitudinal extension of genetic matching, a machine learning approach that automates balancing of covariate histories. We examine performance by comparing the proposed extension against baseline propensity score matching and time-dependent propensity score matching.

METHODS

To evaluate comparative performance, we developed a Monte Carlo simulation framework that reflects a static treatment assigned at multiple time points. Data generation considers a treatment assignment model, a continuous outcome model, and underlying covariates. In simulation, we generated 1,000 datasets, each consisting of 1,000 subjects, and applied: (1) nearest neighbour matching on time-invariant, baseline propensity scores; (2) sequential risk set matching on time-dependent propensity scores; and (3) longitudinal genetic matching on time-dependent covariates. To measure comparative performance, we estimated covariate balance, efficiency, bias, and root mean squared error (RMSE) of treatment effect estimates. In scenario analysis, we varied underlying assumptions for assumed covariate distributions, correlations, treatment assignment models, and outcome models.

RESULTS

In all scenarios, baseline propensity score matching resulted in biased effect estimation in the presence of time-dependent confounding, with mean bias ranging from 29.7% to 37.2%. In contrast, time-dependent propensity score matching and longitudinal genetic matching achieved stronger covariate balance and yielded less biased estimation, with mean bias ranging from 0.7% to 13.7%. Across scenarios, longitudinal genetic matching achieved similar or better performance than time-dependent propensity score matching without requiring manual re-specifications or normality of covariates.

CONCLUSIONS

While the most appropriate longitudinal method will depend on research questions and underlying data patterns, our study can help guide these decisions. Simulation results demonstrate the validity of our longitudinal genetic matching approach for supporting future real-world assessments of treatments accessible at multiple time points.

Identification of lncRNAs Deregulated in Epithelial Ovarian Cancer Based on a Gene Expression Profiling Meta-Analysis

Epithelial ovarian cancer (EOC) is one of the deadliest gynecological cancers worldwide, mainly because of its initially asymptomatic nature and consequently late diagnosis. Long non-coding RNAs (lncRNA) are non-coding transcripts of more than 200 nucleotides, whose deregulation is involved in pathologies such as EOC, and are therefore envisaged as future biomarkers. We present a meta-analysis of available gene expression profiling (microarray and RNA sequencing) studies from EOC patients to identify lncRNA genes with diagnostic and prognostic value. In this meta-analysis, we include 46 independent cohorts, along with available expression profiling data from EOC cell lines. Differential expression analyses were conducted to identify those lncRNAs that are deregulated in (i) EOC versus healthy ovary tissue, (ii) unfavorable versus more favorable prognosis, (iii) metastatic versus primary tumors, (iv) chemoresistant versus chemosensitive EOC, and (v) correlation to specific histological subtypes of EOC. From the results of this meta-analysis, we established a panel of lncRNAs that are highly correlated with EOC. The panel includes several lncRNAs that are already known and even functionally characterized in EOC, but also lncRNAs that have not been previously correlated with this cancer, and which are discussed in relation to their putative role in EOC and their potential use as clinically relevant tools.

PanDrugs2: prioritizing cancer therapies using integrated individual multi-omics data

Genomics studies routinely confront researchers with long lists of tumor alterations detected in patients. Such lists are difficult to interpret since only a minority of the alterations are relevant biomarkers for diagnosis and for designing therapeutic strategies. PanDrugs is a methodology that facilitates the interpretation of tumor molecular alterations and guides the selection of personalized treatments. To do so, PanDrugs scores gene actionability and drug feasibility to provide a prioritized evidence-based list of drugs. Here, we introduce PanDrugs2, a major upgrade of PanDrugs that, in addition to somatic variant analysis, supports a new integrated multi-omics analysis which simultaneously combines somatic and germline variants, copy number variation and gene expression data. Moreover, PanDrugs2 now considers cancer genetic dependencies to extend tumor vulnerabilities providing therapeutic options for untargetable genes. Importantly, a novel intuitive report to support clinical decision-making is generated. PanDrugs database has been updated, integrating 23 primary sources that support >74K drug-gene associations obtained from 4642 genes and 14 659 unique compounds. The database has also been reimplemented to allow semi-automatic updates to facilitate maintenance and release of future versions. PanDrugs2 does not require login and is freely available at https://www.pandrugs.org/.

Overcoming Cancer Multi-drug Resistance (MDR): Reasons, mechanisms, nanotherapeutic solutions, and challenges

Multi-drug resistance (MDR) in cancer cells, either intrinsic or acquired through various mechanisms, significantly hinders the therapeutic efficacy of drugs. Typically, the reduced therapeutic performance of various drugs is predominantly due to the inherent over expression of ATP-binding cassette (ABC) transporter proteins on the cell membrane, resulting in the deprived uptake of drugs, augmenting drug detoxification, and DNA repair. In addition to various physiological abnormalities and extensive blood flow, MDR cancer phenotypes exhibit improved apoptotic threshold and drug efflux efficiency. These severe consequences have substantially directed researchers in the fabrication of various advanced therapeutic strategies, such as co-delivery of drugs along with various generations of MDR inhibitors, augmented dosage regimens and frequency of administration, as well as combinatorial treatment options, among others. In this review, we emphasize different reasons and mechanisms responsible for MDR in cancer, including but not limited to the known drug efflux mechanisms mediated by permeability glycoprotein (P-gp) and other pumps, reduced drug uptake, altered DNA repair, and drug targets, among others. Further, an emphasis on specific cancers that share pathogenesis in executing MDR and effluxed drugs in common is provided. Then, the aspects related to various nanomaterials-based supramolecular programmable designs (organic- and inorganic-based materials), as well as physical approaches (light- and ultrasound-based therapies), are discussed, highlighting the unsolved issues and future advancements. Finally, we summarize the review with interesting perspectives and future trends, exploring further opportunities to overcome MDR.

Homologous recombination deficiency signatures in gastrointestinal and thoracic cancers correlate with platinum therapy duration

There is emerging evidence about the predictive role of homologous recombination deficiency (HRD), but this is less defined in gastrointestinal (GI) and thoracic malignancies. We reviewed whole genome (WGS) and transcriptomic (RNA-Seq) data from advanced GI and thoracic cancers in the Personalized OncoGenomics trial (NCT02155621) to evaluate HRD scores and single base substitution (SBS)3, which is associated with BRCA1/2 mutations and potentially predictive of defective HRD. HRD scores were calculated by sum of loss of heterozygosity, telomeric allelic imbalance, and large-scale state transitions scores. Regression analyses examined the association between HRD and time to progression on platinum (TTPp). We included 223 patients with GI (n = 154) or thoracic (n = 69) malignancies. TTPp was associated with SBS3 (p < 0.01) but not HRD score in patients with GI malignancies, whereas neither was associated with TTPp in thoracic malignancies. Tumors with gBRCA1/2 mutations and a somatic second alteration exhibited high SBS3 and HRD scores, but these signatures were also present in several tumors with germline but no somatic second alterations, suggesting silencing of the wild-type allele or BRCA1/2 haploinsufficiency. Biallelic inactivation of an HR gene, including loss of XRCC2 and BARD1, was identified in BRCA1/2 wild-type HRD tumors and these patients had prolonged response to platinum. Thoracic cases with high HRD score were associated with high RECQL5 expression (p ≤ 0.025), indicating another potential mechanism of HRD. SBS3 was more strongly associated with TTPp in patients with GI malignancies and may be complementary to using HRD and BRCA status in identifying patients who benefit from platinum therapy.

CKLF as a Prognostic Biomarker and Its Association with Immune Infiltration in Hepatocellular Carcinoma

The Chemokine-like factor (CKLF)-like MARVEL transmembrane domain-containing (CMTM) family, comprising nine members, is involved in the tumorigenesis and progression of various cancers. However, the expression profiles and clinical significance of CMTM family members in hepatocellular carcinoma (HCC) are not fully clarified. In this study, the RNA-sequencing and clinical data were downloaded from The Cancer Genome Atlas (TCGA) databases. The Kaplan–Meier method and the Cox proportional hazards regression analysis were used to evaluate the prognostic significance of CMTM family members. Single-sample gene set enrichment analysis (ssGSEA) and ESTIMATE algorithms were employed to explore the relationship between CMTM family genes and the tumor microenvironment in HCC. Finally, the prognostic CMTM family gene expression was further validated by quantitative real-time polymerase chain reaction (qRT-PCR) and immunohistochemical (IHC) staining in clinical HCC tissue specimens. The results indicated that, compared with normal tissues, the expression of CKLF, CMTM1, CMTM3, CMTM4, CMTM7, and CMTM8 were significantly upregulated in HCC, while the expression of CMTM2, CMTM5, and CMTM6 were significantly downregulated in HCC. Univariate and multivariate Cox regression analysis demonstrated that CKLF was an independent prognostic biomarker for the overall survival (OS) of HCC patients. In HCC, the expression of CKLF was found to be correlated with immune cell infiltration, immune-related functions, and immune checkpoint genes. The qRT-PCR and IHC confirmed that CKLF was highly expressed in HCC. Overall, this research suggested that CKLF is involved in immune cell infiltration and may serve as a critical prognostic biomarker, which provides new light on the therapeutics for HCC.

Staphylococcus aureus host interactions and adaptation

Invasive Staphylococcus aureus infections are common, causing high mortality, compounded by the propensity of the bacterium to develop drug resistance. S. aureus is an excellent case study of the potential for a bacterium to be commensal, colonizing, latent or disease-causing; these states defined by the interplay between S. aureus and host. This interplay is multidimensional and evolving, exemplified by the spread of S. aureus between humans and other animal reservoirs and the lack of success in vaccine development. In this Review, we examine recent advances in understanding the S. aureus-host interactions that lead to infections. We revisit the primary role of neutrophils in controlling infection, summarizing the discovery of new immune evasion molecules and the discovery of new functions ascribed to well-known virulence factors. We explore the intriguing intersection of bacterial and host metabolism, where crosstalk in both directions can influence immune responses and infection outcomes. This Review also assesses the surprising genomic plasticity of S. aureus, its dualism as a multi-mammalian species commensal and opportunistic pathogen and our developing understanding of the roles of other bacteria in shaping S. aureus colonization.

Clinical management of molecular alterations identified by high throughput sequencing in patients with advanced solid tumors in treatment failure: Real-world data from a French hospital

Background

In the context of personalized medicine, screening patients to identify targetable molecular alterations is essential for therapeutic decisions such as inclusion in clinical trials, early access to therapies, or compassionate treatment. The objective of this study was to determine the real-world impact of routine incorporation of FoundationOne analysis in cancers with a poor prognosis and limited treatment options, or in those progressing after at least one course of standard therapy.

Methods

A FoundationOneCDx panel for solid tumor or liquid biopsy samples was offered to 204 eligible patients.

Results

Samples from 150 patients were processed for genomic testing, with a data acquisition success rate of 93%. The analysis identified 2419 gene alterations, with a median of 11 alterations per tumor (range, 0-86). The most common or likely pathogenic variants were on TP53, TERT, PI3KCA, CDKN2A/B, KRAS, CCDN1, FGF19, FGF3, and SMAD4. The median tumor mutation burden was three mutations/Mb (range, 0-117) in 143 patients with available data. Of 150 patients with known or likely pathogenic actionable alterations, 13 (8.6%) received matched targeted therapy. Sixty-nine patients underwent Molecular Tumor Board, which resulted in recommendations in 60 cases. Treatment with genotype-directed therapy had no impact on overall survival (13 months vs. 14 months; p = 0.95; hazard ratio = 1.04 (95% confidence interval, 0.48-2.26)].

Conclusions

This study highlights that an organized center with a Multidisciplinary Molecular Tumor Board and an NGS screening system can obtain satisfactory results comparable with those of large centers for including patients in clinical trials.

Towards clinical implementation of circulating tumor DNA in metastatic prostate cancer: Opportunities for integration and pitfalls to interpretation

Plasma circulating tumor DNA (ctDNA) represents short fragments of tumor-derived DNA released into the bloodstream primarily from cancer cells undergoing apoptosis. In metastatic castration-resistant prostate cancer (mCRPC), characterizing genomic alterations in ctDNA identifies mutations, copy number alterations, and structural rearrangements with predictive and prognostic biomarker utility. These associations with clinical outcomes have resulted in ctDNA increasingly incorporated into routine clinical care. In this review, we summarize current and emerging applications for ctDNA analysis in metastatic prostate cancer, including outcome prediction, treatment selection, and characterization of treatment resistance. We also discuss potential pitfalls with interpreting ctDNA findings, namely false negatives arising from low tumor content and optimal assay design, including correction for clonal hematopoiesis of indeterminate potential and germline variants. Understanding the influence of these limitations on interpretation of ctDNA results is necessary to overcome barriers to clinical implementation. Nevertheless, as assay availability and technology continue to improve, recognizing both opportunities and shortcomings of ctDNA analysis will retain relevance with informing the implementation of precision-oncology initiatives for metastatic prostate cancer.

Access and quality of biomarker testing for precision oncology in Europe

BACKGROUND

Predictive biomarkers are essential for selecting the best therapeutic strategy in patients with cancer. The International Quality Network for Pathology, the European Cancer Patient Coalition and the European Federation of Pharmaceuticals Industries and Associations evaluated the access to and quality of biomarker testing across Europe.

METHODS

Data sources included surveys of 141 laboratory managers and 1.665 patients, and 58 in-depth interviews with laboratory managers, physicians and payers. Four access metrics (laboratory access, test availability, test reimbursement, test order rate) and three quality metrics (quality scheme participation, laboratory accreditation, test turnaround time) were applied to rank the results.

RESULTS

The access to precision medicines is higher in countries with public national reimbursement processes in place. Lack of diagnostic laboratory infrastructure, inefficient organization and/or insufficient public reimbursement narrow the access to single biomarker tests in many European countries. In countries with limited public reimbursement, pharma and patients' out of pocket were the primary funding sources for testing. Uptake of multi-biomarker next generation sequencing (NGS) is highly varied, ranging from 0% to >50%. Financial constraints, a lack of NGS testing capabilities and the failure to include NGS testing in the guidelines represent the main barriers to NGS implementation. The quality of biomarker testing is highest in Western and Northern Europe, with more than 90% of laboratories participating in quality assurance schemes.

CONCLUSIONS

Our data clearly indicate the need for a call to action to ensure the clinical implementation of precision medicine in Europe.

Big data in basic and translational cancer research

Historically, the primary focus of cancer research has been molecular and clinical studies of a few essential pathways and genes. Recent years have seen the rapid accumulation of large-scale cancer omics data catalysed by breakthroughs in high-throughput technologies. This fast data growth has given rise to an evolving concept of 'big data' in cancer, whose analysis demands large computational resources and can potentially bring novel insights into essential questions. Indeed, the combination of big data, bioinformatics and artificial intelligence has led to notable advances in our basic understanding of cancer biology and to translational advancements. Further advances will require a concerted effort among data scientists, clinicians, biologists and policymakers. Here, we review the current state of the art and future challenges for harnessing big data to advance cancer research and treatment.