Tracking Cancer Evolution through the Disease Course

Breast cancer: pathogenesis and treatments

Breast cancer, characterized by unique epidemiological patterns and significant heterogeneity, remains one of the leading causes of malignancy-related deaths in women. The increasingly nuanced molecular subtypes of breast cancer have enhanced the comprehension and precision treatment of this disease. The mechanisms of tumorigenesis and progression of breast cancer have been central to scientific research, with investigations spanning various perspectives such as tumor stemness, intra-tumoral microbiota, and circadian rhythms. Technological advancements, particularly those integrated with artificial intelligence, have significantly improved the accuracy of breast cancer detection and diagnosis. The emergence of novel therapeutic concepts and drugs represents a paradigm shift towards personalized medicine. Evidence suggests that optimal diagnosis and treatment models tailored to individual patient risk and expected subtypes are crucial, supporting the era of precision oncology for breast cancer. Despite the rapid advancements in oncology and the increasing emphasis on the clinical precision treatment of breast cancer, a comprehensive update and summary of the panoramic knowledge related to this disease are needed. In this review, we provide a thorough overview of the global status of breast cancer, including its epidemiology, risk factors, pathophysiology, and molecular subtyping. Additionally, we elaborate on the latest research into mechanisms contributing to breast cancer progression, emerging treatment strategies, and long-term patient management. This review offers valuable insights into the latest advancements in Breast Cancer Research, thereby facilitating future progress in both basic research and clinical application.

ZACN Associated with Poor Prognosis Promotes Proliferation of Kidney Renal Clear Cell Carcinoma Cells by Inhibiting JTC801-Induced Alkaliptosis

Alkaliptosis, crucial in various cancers, is a specific form of cell death. This study aims to screen a prognosis-related gene in kidney renal clear cell carcinoma (KIRC) using the alkaliptosis gene set and to investigate the roles of the gene in KIRC and its association with alkaliptosis. Transcriptome and clinical information of KIRC patients were collected from the TCGA-KIRC and GSE29609 database. We detected ZACN levels in normal kidney cells and KIRC cells and assessed the ZACN and JTC801-induced alkaliptosis relationship using immunoblotting and pH measurement. In the alkaliptosis gene set (IKBKB, NFKB1, CA9, CHUK, IKBKG, and RELA), NFKB1, CHUK, and IKBKG exhibited differential expression in TCGA-KIRC. Based on these three genes, two alkaliptosis patterns were identified in TCGA-KIRC. The independent prognostic gene for KIRC, ZACN, was screened. High ZACN in KIRC patients indicated a poor prognosis. ZACN was inversely related to the infiltration of anti-cancer immune cells such as CD4 + T cells, macrophages, and neutrophils, and it regulated the immune checkpoint and gene mutations. Patients characterized by high ZACN levels exhibited a heightened drug sensitivity to ABT737_1910, 5-Fluorouracil_1073, etc. ZACN expression in KIRC cells was increased relative to normal kidney cells and was inhibited in a concentration-dependent manner by JTC801. ZACN overexpression suppressed p-p65/p65 expression, increased expression of CA9, and lowered intracellular pH. In KIRC, ZACN inhibits JTC801-induced alkaliptosis. This study sheds light on a novel mechanism involving ZACN and alkaliptosis in KIRC, offering a promising avenue for further research and potential therapeutic interventions in KIRC management.

Early Cancer Detection Through Comprehensive Mapping of Dynamic Tumorigenesis

Current strategies for early cancer detection and diagnosis need updating to achieve greater precision, necessitating the creation of a comprehensive evolutionary map of tumorigenesis. This requires establishing high-quality prospective cohorts, systematically collecting samples for integrated spatiotemporal multiomics analyses, and efficiently translating laboratory findings into clinical applications.

Optimal systemic treatment and real-world clinical application of ctDNA in patients with metastatic HER2-mutant lung cancer

INTRODUCTION

No definitive answers currently exist regarding optimal first-line therapy for HER2-mutant NSCLC. Access to rapid tissue sequencing is a major barrier to precision drug development in the first-line setting. ctDNA analysis has the potential to overcome these obstacles and guide treatment.

METHODS

We retrospectively analyzed patients with metastatic HER2-mutant NSCLC who underwent prospective clinical ctDNA sequencing and received systemic therapy at Memorial Sloan Kettering Cancer Center (MSK) from January 2016 to September 2022. HER2 mutations were identified by next-generation sequencing through MSK-IMPACT, MSK-ACCESS or Resolution ctDx LungTM assay. Primary endpoints were time to the next treatment (TTNT) and overall survival (OS).

RESULTS

Sixty-three patients were included in the primary analysis. Chemoimmunotherapy (33/63, 52.4 %) was the predominant first-line treatment with a median TTNT of 5.1 months (95 %CI 4.1 - 6.1) whereas 55.0 % (22/40) of patients who received second-line T-DXd obtained a median TTNT of 9.2 m (95 % CI, 0-22.2). Plasma ctDNA was tested before first-line therapy in 40 patients with a median OS of 28.0 months (95 % CI 21-34), in whom 31 patients (78.0 %) had detectable ctDNA. HER2 mutations were detected on ctDNA with a median turnaround time of 13 days, occasionally co-occurred with EGFR and MET alterations and were tracked longitudinally correlating with treatment response. Patients with detectable baseline ctDNA had significantly shorter OS (hazard ratio (HR), 5.25; 95 % CI, 1.2-23.9; p = 0.019).

CONCLUSION

Chemoimmunotherapy remains a major treatment option for metastatic HER2-mutant NSCLC. ctDNA can rapidly detect HER2 and co-mutations, and it has the potential to guide and monitor optimal first-line therapy. As a negative prognostic biomarker, detectable ctDNA at baseline would need to be taken into account for patient selection in future studies.

Oncogenic composite mutations can be predicted by co-mutations and their chromosomal location

Genetic heterogeneity in tumors can show a remarkable selectivity when two or more independent genetic events occur in the same gene. This phenomenon, called composite mutation, points toward a selective pressure, which frequently causes therapy resistance to mutation-specific drugs. Since composite mutations have been described to occur in sub-clonal populations, they are not always captured through biopsy sampling. Here, we provide a proof of concept to predict composite mutations to anticipate which patients might be at risk for sub-clonally driven therapy resistance. We found that composite mutations occur in 5% of cancer patients, mostly affecting the PIK3CA, EGFR, BRAF, and KRAS genes, which are common precision medicine targets. Furthermore, we found a strong and significant relationship between the frequencies of composite mutations with commonly co-occurring mutations in a non-composite context. We also found that co-mutations are significantly enriched on the same chromosome. These observations were independently confirmed using cell line data. Finally, we show the feasibility of predicting compositive mutations based on their co-mutations (AUC 0.62, 0.81, 0.82, and 0.91 for EGFR, PIK3CA, KRAS, and BRAF, respectively). This prediction model could help to stratify patients who are at risk of developing therapy resistance-causing mutations.

Longitudinal deep neural networks for assessing metastatic brain cancer on a large open benchmark

The detection and tracking of metastatic cancer over the lifetime of a patient remains a major challenge in clinical trials and real-world care. Advances in deep learning combined with massive datasets may enable the development of tools that can address this challenge. We present NYUMets-Brain, the world's largest, longitudinal, real-world dataset of cancer consisting of the imaging, clinical follow-up, and medical management of 1,429 patients. Using this dataset we developed Segmentation-Through-Time, a deep neural network which explicitly utilizes the longitudinal structure of the data and obtained state-of-the-art results at small (<10 mm3) metastases detection and segmentation. We also demonstrate that the monthly rate of change of brain metastases over time are strongly predictive of overall survival (HR 1.27, 95%CI 1.18-1.38). We are releasing the dataset, codebase, and model weights for other cancer researchers to build upon these results and to serve as a public benchmark.

Heat shock transcription factor 1 facilitates liver cancer progression by driving super-enhancer-mediated transcription of MYCN

BACKGROUND

Heat shock transcription factors (HSFs) play crucial roles in the development of malignancies. However, the specific roles of HSFs in hepatocellular carcinoma (HCC) have yet to be fully elucidated.

AIMS

To explore the involvement of the HSF family, particularly HSF1, in the progression and prognosis of HCC.

MATERIALS & METHODS

We conducted a thorough analysis of HSF expression and copy number variations across various cancer datasets. Specifically focusing on HSF1, we examined its expression levels and prognostic implications in HCC. In vitro and in vivo experiments were carried out to evaluate the impact of HSF1 on liver cancer cell proliferation. Additionally, we utilized CUT&Tag, H3K27 acetylation enrichment, and RNA sequencing (RNA-seq) to investigate the super-enhancer (SE) regulatory landscapes of HSF1 in liver cancer cell lines.

RESULTS

HSF1 expression is elevated in HCC and is linked to poor prognosis in several datasets. HSF1 stimulates liver cancer cell proliferation both in vitro and in vivo, partly through modulation of H3K27ac levels, influencing enhancer distribution. Mechanistically, our findings demonstrate that HSF1 transcriptionally activates MYCN expression by binding to its promoter and SE elements, thereby promoting liver cancer cell proliferation. Moreover, increased MYCN expression was detected in HCC tumors and correlated with unfavorable patient outcomes.

DISCUSSION

Our study sheds light on previously unexplored aspects of HSF1 biology, identifying it as a transcription factor capable of shaping the epigenetic landscape in the context of HCC. Given HSF1's potential as an epigenetic regulator, targeting the HSF1-MYCN axis could open up new therapeutic possibilities for HCC treatment.

CONCLUSION

The HSF1-MYCN axis constitutes a transcription-dependent regulatory mechanism that may function as both a prognostic indicator and a promising therapeutic target in liver cancer. Further exploration of this axis could yield valuable insights into novel treatment strategies for HCC.

Ecological and evolutionary dynamics to design and improve ovarian cancer treatment

Ovarian cancer ecosystems are exceedingly complex, consisting of a high heterogeneity of cancer cells. Development of drugs such as poly ADP-ribose polymerase (PARP) inhibitors, targeted therapies and immunotherapies offer more options for sequential or combined treatments. Nevertheless, mortality in metastatic ovarian cancer patients remains high because cancer cells consistently develop resistance to single and combination therapies, urging a need for treatment designs that target the evolvability of cancer cells. The evolutionary dynamics that lead to resistance emerge from the complex tumour microenvironment, the heterogeneous populations, and the individual cancer cell's plasticity. We propose that successful management of ovarian cancer requires consideration of the ecological and evolutionary dynamics of the disease. Here, we review current options and challenges in ovarian cancer treatment and discuss principles of tumour evolution. We conclude by proposing evolutionarily designed strategies for ovarian cancer, with the goal of integrating such principles with longitudinal, quantitative data to improve the treatment design and management of drug resistance. KEY POINTS/HIGHLIGHTS: Tumours are ecosystems in which cancer and non-cancer cells interact and evolve in complex and dynamic ways. Conventional therapies for ovarian cancer inevitably lead to the development of resistance because they fail to consider tumours' heterogeneity and cellular plasticity. Eco-evolutionarily designed therapies should consider cancer cell plasticity and patient-specific characteristics to improve clinical outcome and prevent relapse.

Impact of the COVID-19 Pandemic on the Diagnosis of Malignant Neoplasia of the Bronchus and Lung in the Burgos Region

PURPOSE

To retrospectively analyze the impact of the COVID-19 pandemic on the diagnosis, mortality rate, and survival period of malignant bronchial and lung neoplasms in the Burgos region, with the aim of promoting the development of strategies to improve cancer care management during health crises, highlighting the importance of non-pharmacological approaches to mitigate the negative impacts of future pandemics on lung cancer patients.

METHODS

This retrospective, longitudinal, single-center study was conducted in Burgos from 2019 to 2021. Participants included all patients diagnosed with malignant bronchial and lung neoplasms by the Pneumology unit of Complejo Asistencial Universitario de Burgos during the year immediately before and the year immediately after 31 March 2020, the official start date of the pandemic. Inclusion criteria encompassed patients diagnosed through histological or clinicoradiological methods, who provided informed consent. Data were systematically gathered using a specific template that included demographic information, disease stage, death, and survival time. Statistical analysis involved descriptive methods, ANOVA, and chi-square tests to assess differences in survival time and associations between categorical variables.

RESULTS

The results reveal a decrease in the number of patients diagnosed during the pandemic period (154 vs. 105), which could indicate delays in detection. However, there were no significant differences between the two periods, in which more than 60% of cases were detected in stage IV, being incompatible with survival. Although fewer patients died during the pandemic than expected (p = 0.015), patients diagnosed after the onset of the pandemic had a shorter survival time (182.43 ± 142.63 vs. 253.61 ± 224.30; p = 0.038). Specifically, those diagnosed in stage I during the pre-pandemic had a much longer survival time (741.50 days) than the rest of the patients (p < 0.05). In addition, among those diagnosed in stage IV, those diagnosed after the beginning of the pandemic had a shorter survival time (157.29 ± 202.36 vs. 241.18 ± 218.36; p = 0.026).

CONCLUSIONS

Understanding these changes can support both medical strategies and non-pharmacological therapies to improve cancer care management during health crises, thus contributing to the optimization of public health.

Mutational and transcriptional profile predicts the prognosis of stage IV gastric cancer - Prognostic factors for metastatic gastric cancer

BACKGROUND AND STUDY AIMS

The clinicopathological risk factors in the prognosis of stage IV gastric cancer have been comprehensively studied. However, the influencing factors of stage IV gastric cancer prognosis at genomic and transcriptional levels have not been well defined.

PATIENTS AND METHODS

The mutational and transcriptional data, along with demographic, clinicopathological and prognostic information of 44 stage IV gastric cancer patients were downloaded from the TCGA database. Univariate and multivariate analyses were performed to identify the significant risk factors and a Nomogram model was established to predict the patient prognosis.

RESULTS

TTN, TP53, FLG, LRP1B, SYNE1 and ARID1A were among the top mutated genes without hot-spot mutations. The mutational status of AHNAK2, ASCC3, DNAH3, DOP1A, MYLK, SIPA1L1, SORBS2, SYNE1 and ANF462 significantly stratified the patient prognosis. The transcription of several genes, such as AQP10, HOXC8/9/10, COL10A1/COL11A1, WNT7B, KRT17 and KLK6 was significantly up-regulated or down-regulated. Enrichment analysis on mutations and transcription revealed cell skeleton and membrane function, extracellular matrix function, HPV infection, and several cancer-related pathways as the main aberrancies. Univariate analyses revealed a series of significant factors stratifying patient prognosis, mainly including cancer location, several mutated genes and many up- or down-regulated genes. However, subsequent multivariate analysis revealed SYNE1 mutation, DNAH3 mutation, COMMD3 transcription level, and cancer location as the independent risk factors. A Nomogram model has been established with these significant risk factors to predict the patient prognosis. Further validation is needed to ensure the effectiveness of the model in real clinical practice.

CONCLUSIONS

Cancer location, along with the mutational status of SYNE1 and DNAH3 and the transcriptional level of COMMD3 were independent risk factors of stage IV gastric cancer. A Nomogram model was established with these factors for prognosis prediction.

Clinical application of ctDNA in early diagnosis, treatment and prognosis of patients with non-small cell lung cancer

Lung cancer is one of the most common malignancies worldwide, with non-small cell lung cancer (NSCLC) being the most common type. As understanding of precise treatment options for NSCLC deepens, circulating tumor DNA (ctDNA) has emerged as a potential biomarker that has become a research hotspot and may represent a new approach for the individualized diagnosis and treatment of NSCLC. This article reviews the applications of ctDNA for the early screening of patients with NSCLC, guiding targeted therapy and immunotherapy, evaluating chemotherapy and postoperative efficacy, assessing prognosis and monitoring recurrence. With the in-depth study of the pathogenesis of NSCLC, plasma ctDNA may become an indispensable part of the precise treatment of NSCLC, which has great clinical application prospects.

Programmed Death Ligand-1 and Tumor Mutation Burden Testing of Patients With Lung Cancer for Selection of Immune Checkpoint Inhibitor Therapies: Guideline From the College of American Pathologists, Association for Molecular Pathology, International Association for the Study of Lung Cancer, Pulmonary Pathology Society, and LUNGevity Foundation

CONTEXT.—

Rapid advancements in the understanding and manipulation of tumor-immune interactions have led to the approval of immune therapies for patients with non-small cell lung cancer. Certain immune checkpoint inhibitor therapies require the use of companion diagnostics, but methodologic variability has led to uncertainty around test selection and implementation in practice.

OBJECTIVE.—

To develop evidence-based guideline recommendations for the testing of immunotherapy/immunomodulatory biomarkers, including programmed death ligand-1 (PD-L1) and tumor mutation burden (TMB), in patients with lung cancer.

DESIGN.—

The College of American Pathologists convened a panel of experts in non-small cell lung cancer and biomarker testing to develop evidence-based recommendations in accordance with the standards for trustworthy clinical practice guidelines established by the National Academy of Medicine. A systematic literature review was conducted to address 8 key questions. Using the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) approach, recommendations were created from the available evidence, certainty of that evidence, and key judgments as defined in the GRADE Evidence to Decision framework.

RESULTS.—

Six recommendation statements were developed.

CONCLUSIONS.—

This guideline summarizes the current understanding and hurdles associated with the use of PD-L1 expression and TMB testing for immune checkpoint inhibitor therapy selection in patients with advanced non-small cell lung cancer and presents evidence-based recommendations for PD-L1 and TMB testing in the clinical setting.

The Evolving Landscape of Biomarkers for Immune Checkpoint Blockade in Genitourinary Cancers

In the past decade, immune checkpoint inhibitors (ICI) have been approved for treatment of genitourinary malignancies and have revolutionized the treatment landscape of these tumors. However, despite the remarkable success of these therapies in some GU malignancies, many patients' tumors do not respond to these therapies, and others may experience significant side effects, such as immune-related adverse events (iRAEs). Accordingly, biomarkers and improved prognostic tools are critically needed to help predict which patients will respond to ICI, predict and mitigate risk of developing immune-related adverse events, and inform personalized choice of therapy for each patient. Ongoing clinical and preclinical studies continue to provide an increasingly robust understanding of the mechanisms of the response to immunotherapy, which continue to inform biomarker development and validation. Herein, we provide a comprehensive review of biomarkers of the response to immunotherapy in GU tumors and their role in selection of therapy and disease monitoring.

Decoding the interplay between genetic and non-genetic drivers of metastasis

Metastasis is a multistep process by which cancer cells break away from their original location and spread to distant organs, and is responsible for the vast majority of cancer-related deaths. Preventing early metastatic dissemination would revolutionize the ability to fight cancer. Unfortunately, the relatively poor understanding of the molecular underpinnings of metastasis has hampered the development of effective anti-metastatic drugs. Although it is now accepted that disseminating tumour cells need to acquire multiple competencies to face the many obstacles they encounter before reaching their metastatic site(s), whether these competencies are acquired through an accumulation of metastasis-specific genetic alterations and/or non-genetic events is often debated. Here we review a growing body of literature highlighting the importance of both genetic and non-genetic reprogramming events during the metastatic cascade, and discuss how genetic and non-genetic processes act in concert to confer metastatic competencies. We also describe how recent technological advances, and in particular the advent of single-cell multi-omics and barcoding approaches, will help to better elucidate the cross-talk between genetic and non-genetic mechanisms of metastasis and ultimately inform innovative paths for the early detection and interception of this lethal process.

Circulating tumour DNA detects somatic variants contributing to spatial and temporal intra-tumoural heterogeneity in head and neck squamous cell carcinoma

Background

As circulating tumour DNA (ctDNA) liquid biopsy analysis is increasingly incorporated into modern oncological practice, establishing the impact of genomic intra-tumoural heterogeneity (ITH) upon data output is paramount. Despite advances in other cancer types the evidence base in head and neck squamous cell carcinoma (HNSCC) remains poor. We sought to investigate the utility of ctDNA to detect ITH in HNSCC.

Methods

In a pilot cohort of 9 treatment-naïve HNSCC patients, DNA from two intra-tumoural sites (core and margin) was whole-exome sequenced. A 9-gene panel was designed to perform targeted sequencing on pre-treatment plasma cell-free DNA and selected post-treatment samples.

Results

Rates of genomic ITH among the 9 patients was high. COSMIC variants from 19 TCGA HNSCC genes demonstrated an 86.9% heterogeneity rate (present in one tumour sub-site only). Across all patients, cell-free DNA (ctDNA) identified 12.9% (range 7.5-19.8%) of tumour-specific variants, of which 55.6% were specific to a single tumour sub-site only. CtDNA identified 79.0% (range: 55.6-90.9%) of high-frequency variants (tumour VAF>5%). Analysis of ctDNA in serial post-treatment blood samples in patients who suffered recurrence demonstrated dynamic changes in both tumour-specific and acquired variants that predicted recurrence ahead of clinical detection.

Conclusion

We demonstrate that a ctDNA liquid biopsy identified spatial genomic ITH in HNSCC and reliably detected high-frequency driver mutations. Serial sampling allowed post-treatment surveillance and early identification of treatment failure.

Contributions of transcriptional noise to leukaemia evolution: KAT2A as a case-study

Transcriptional noise is proposed to participate in cell fate changes, but contributions to mammalian cell differentiation systems, including cancer, remain associative. Cancer evolution is driven by genetic variability, with modulatory or contributory participation of epigenetic variants. Accumulation of epigenetic variants enhances transcriptional noise, which can facilitate cancer cell fate transitions. Acute myeloid leukaemia (AML) is an aggressive cancer with strong epigenetic dependencies, characterized by blocked differentiation. It constitutes an attractive model to probe links between transcriptional noise and malignant cell fate regulation. Gcn5/KAT2A is a classical epigenetic transcriptional noise regulator. Its loss increases transcriptional noise and modifies cell fates in stem and AML cells. By reviewing the analysis of KAT2A-depleted pre-leukaemia and leukaemia models, I discuss that the net result of transcriptional noise is diversification of cell fates secondary to alternative transcriptional programmes. Cellular diversification can enable or hinder AML progression, respectively, by differentiation of cell types responsive to mutations, or by maladaptation of leukaemia stem cells. KAT2A-dependent noise-responsive genes participate in ribosome biogenesis and KAT2A loss destabilizes translational activity. I discuss putative contributions of perturbed translation to AML biology, and propose KAT2A loss as a model for mechanistic integration of transcriptional and translational control of noise and fate decisions. This article is part of a discussion meeting issue 'Causes and consequences of stochastic processes in development and disease'.

The two sides of chromosomal instability: drivers and brakes in cancer

Chromosomal instability (CIN) is a hallmark of cancer and is associated with tumor cell malignancy. CIN triggers a chain reaction in cells leading to chromosomal abnormalities, including deviations from the normal chromosome number or structural changes in chromosomes. CIN arises from errors in DNA replication and chromosome segregation during cell division, leading to the formation of cells with abnormal number and/or structure of chromosomes. Errors in DNA replication result from abnormal replication licensing as well as replication stress, such as double-strand breaks and stalled replication forks; meanwhile, errors in chromosome segregation stem from defects in chromosome segregation machinery, including centrosome amplification, erroneous microtubule-kinetochore attachments, spindle assembly checkpoint, or defective sister chromatids cohesion. In normal cells, CIN is deleterious and is associated with DNA damage, proteotoxic stress, metabolic alteration, cell cycle arrest, and senescence. Paradoxically, despite these negative consequences, CIN is one of the hallmarks of cancer found in over 90% of solid tumors and in blood cancers. Furthermore, CIN could endow tumors with enhanced adaptation capabilities due to increased intratumor heterogeneity, thereby facilitating adaptive resistance to therapies; however, excessive CIN could induce tumor cells death, leading to the "just-right" model for CIN in tumors. Elucidating the complex nature of CIN is crucial for understanding the dynamics of tumorigenesis and for developing effective anti-tumor treatments. This review provides an overview of causes and consequences of CIN, as well as the paradox of CIN, a phenomenon that continues to perplex researchers. Finally, this review explores the potential of CIN-based anti-tumor therapy.

Spatial transcriptomics and the anatomical pathologist: Molecular meets morphology

In recent years anatomical pathology has been revolutionised by the incorporation of molecular findings into routine diagnostic practice, and in some diseases the presence of specific molecular alterations are now essential for diagnosis. Spatial transcriptomics describes a group of technologies that provide up to transcriptome-wide expression profiling while preserving the spatial origin of the data, with many of these technologies able to provide these data using a single tissue section. Spatial transcriptomics allows expression profiling of highly specific areas within a tissue section potentially to subcellular resolution, and allows correlation of expression data with morphology, tissue type and location relative to other structures. While largely still research laboratory-based, several spatial transcriptomics methods have now achieved compatibility with formalin-fixed paraffin-embedded tissue (FFPE), allowing their use in diagnostic tissue samples, and with further development potentially leading to their incorporation in routine anatomical pathology practice. This mini review provides an overview of spatial transcriptomics methods, with an emphasis on platforms compatible with FFPE tissue, approaches to assess the data and potential applications in anatomical pathology practice.

Measures of genetic diversification in somatic tissues at bulk and single-cell resolution

Intra-tissue genetic heterogeneity is universal to both healthy and cancerous tissues. It emerges from the stochastic accumulation of somatic mutations throughout development and homeostasis. By combining population genetics theory and genomic information, genetic heterogeneity can be exploited to infer tissue organization and dynamics in vivo. However, many basic quantities, for example the dynamics of tissue-specific stem cells remain difficult to quantify precisely. Here, we show that single-cell and bulk sequencing data inform on different aspects of the underlying stochastic processes. Bulk-derived variant allele frequency spectra (VAF) show transitions from growing to constant stem cell populations with age in samples of healthy esophagus epithelium. Single-cell mutational burden distributions allow a sample size independent measure of mutation and proliferation rates. Mutation rates in adult hematopietic stem cells are higher compared to inferences during development, suggesting additional proliferation-independent effects. Furthermore, single-cell derived VAF spectra contain information on the number of tissue-specific stem cells. In hematopiesis, we find approximately 2 × 105 HSCs, if all stem cells divide symmetrically. However, the single-cell mutational burden distribution is over-dispersed compared to a model of Poisson distributed random mutations. A time-associated model of mutation accumulation with a constant rate alone cannot generate such a pattern. At least one additional source of stochasticity would be needed. Possible candidates for these processes may be occasional bursts of stem cell divisions, potentially in response to injury, or non-constant mutation rates either through environmental exposures or cell-intrinsic variation.

Cancer Evolution: A Multifaceted Affair

Cancer cells adapt and survive through the acquisition and selection of molecular modifications. This process defines cancer evolution. Building on a theoretical framework based on heritable genetic changes has provided insights into the mechanisms supporting cancer evolution. However, cancer hallmarks also emerge via heritable nongenetic mechanisms, including epigenetic and chromatin topological changes, and interactions between tumor cells and the tumor microenvironment. Recent findings on tumor evolutionary mechanisms draw a multifaceted picture where heterogeneous forces interact and influence each other while shaping tumor progression. A comprehensive characterization of the cancer evolutionary toolkit is required to improve personalized medicine and biomarker discovery.

SIGNIFICANCE

Tumor evolution is fueled by multiple enabling mechanisms. Importantly, genetic instability, epigenetic reprogramming, and interactions with the tumor microenvironment are neither alternative nor independent evolutionary mechanisms. As demonstrated by findings highlighted in this perspective, experimental and theoretical approaches must account for multiple evolutionary mechanisms and their interactions to ultimately understand, predict, and steer tumor evolution.

Molecular pathology of non-small cell carcinoma

Currently, lung cancer is treated by the highest number of therapeutic options and the benefits are based on multiple large-scale sequencing studies, translational research and new drug development, which has promoted our understanding of the molecular pathology of lung cancer. According to the driver alterations, different characteristics have been revealed, such as differences in ethnic prevalence, median age and alteration patterns. Consequently, beyond traditional chemoradiotherapy, molecular-targeted therapy and treatment with immune check-point inhibitors (ICI) also became available major therapeutic options. Interestingly, clinical results suggest that the recently established therapies target distinct lung cancer proportions, particularly between the EGFR/ALK and PD-1/PD-L1-positive subsets, e.g. the kinase inhibitors target driver mutation-positive tumours, whereas driver mutation-negative tumours respond to ICI treatment. These therapeutic efficacy-related differences might be explained by the molecular pathogenesis of lung cancer. Addictive driver mutations promote tumour formation with powerful transformation performance, resulting in a low tumour mutation burden, reduced immune surveillance, and subsequent poor response to ICIs. In contrast, regular tobacco smoke exposure repeatedly injures the proximal airway epithelium, leading to accumulated genetic alterations. In the latter pathway, overgrowth due to alteration and immunological exclusion against neoantigens is initially balanced. However, tumours could be generated from certain clones that outcompete immunological exclusion and outgrow the others. Consequently, this cancer type responds to immune check-point treatment. These pathogenic differences are explained well by the two-compartment model, focusing upon the anatomical and functional composition of distinct cellular components between the terminal respiratory unit and the air-conducting system.

An advanced NSCLC patient with ALK-RNF144A and HIP1-ALK fusions treated with ALK-TKI combination therapy: a case report

Background

Anaplastic lymphoma kinase (ALK) rearrangement is one of the most important drivers in non-small cell lung cancer (NSCLC). Despite the effectiveness to canonical 3'-ALK fusions, the clinical efficacy of ALK inhibitors in patients with complex ALK fusions, such as nonreciprocal/reciprocal translocation remains uncertain. Exploring the optimal therapeutic regimens for this subset of patients is of crucial clinical significance.

Case Description

We reported a female patient diagnosed with stage IVB lung adenocarcinoma (LUAD) harboring a novel ALK-RNF144A fusion, concurrent with a Huntingtin-interacting protein 1 (HIP1)-ALK fusion and a RB1 loss-of-function variant. The patient sequentially received multiple lines of treatment with ALK-tyrosine kinase inhibitor (TKI), chemotherapy, radiotherapy and ALK-TKI combined with anti-angiogenesis. Disease progression accompanied by a squamous cell carcinoma transformation was indicated after ALK-TKI combined with anti-angiogenesis and both ALK-RNF144A and HIP1-ALK fusions were retained in the tumor. The patient was subsequently treated with a third generation ALK-TKI, lorlatinib, in combination with albumin-bound paclitaxel and anlotinib, and then achieved stable disease. The patient remained on the treatment as of the last follow-up resulting in an overall survival (OS) of more than 18 months.

Conclusions

We have reported an advanced NSCLC patient with a complex nonreciprocal/reciprocal ALK translocation containing a novel ALK-RNF144A fusion, concurrent with a RB1 loss-of-function mutation, who subsequently experienced pathological squamous cell carcinoma transformation. The combined treatment with ALK-TKI, chemotherapy, and anti-angiogenesis demonstrates clinical efficacy and may provide optional therapeutic strategies for this phenotype.

Early Evolution in Cancer: A Mathematical Support for Pathological and Genomic Evidence in Clear Cell Renal Cell Carcinoma

Clear cell renal cell carcinoma (CCRCC) is an aggressive form of cancer and a paradigmatic example of intratumor heterogeneity (ITH). The hawk-dove game is a mathematical tool designed to analyze competition in biological systems. Using this game, the study reported here analyzes the early phase of CCRCC development, comparing clonal fitness in homogeneous (linear evolutionary) and highly heterogeneous (branching evolutionary) models. Fitness in the analysis is a measure of tumor aggressiveness. The results show that the fittest clone in a heterogeneous environment is fitter than the clone in a homogeneous context in the early phases of tumor evolution. Early and late periods of tumor evolution in CCRCC are also compared. The study shows the convergence of mathematical, histological, and genomics studies with respect to clonal aggressiveness in different periods of the natural history of CCRCC. Such convergence highlights the importance of multidisciplinary approaches for obtaining a better understanding of the intricacies of cancer.

Molecular and functional profiling of chemotolerant cells unveils nucleoside metabolism-dependent vulnerabilities in medulloblastoma

Chemotherapy resistance is considered one of the main causes of tumor relapse, still challenging researchers for the identification of the molecular mechanisms sustaining its emergence. Here, we setup and characterized chemotherapy-resistant models of Medulloblastoma (MB), one of the most lethal pediatric brain tumors, to uncover targetable vulnerabilities associated to their resistant phenotype. Integration of proteomic, transcriptomic and kinomic data revealed a significant deregulation of several pathways in resistant MB cells, converging to cell metabolism, RNA/protein homeostasis, and immune response, eventually impacting on patient outcome. Moreover, resistant MB cell response to a large library of compounds through a high-throughput screening (HTS), highlighted nucleoside metabolism as a relevant vulnerability of chemotolerant cells, with peculiar antimetabolites demonstrating increased efficacy against them and even synergism with conventional chemotherapeutics. Our results suggest that drug-resistant cells significantly rewire multiple cellular processes, allowing their adaptation to a chemotoxic environment, nevertheless exposing alternative actionable susceptibilities for their specific targeting.

Plasma exosomal miR-1290 and miR-29c-3p as diagnostic biomarkers for lung cancer

Background

Enhancing the diagnostic efficacy of early-stage lung cancer is crucial for improving prognosis. The objective of this study was to ascertain dependable exosomal miRNAs as biomarkers for the diagnosis of lung cancer.

Methods

Exosomal miRNA candidates were identified through miRNA sequencing and subsequently validated in various case-control sets using real-time quantitative reverse transcription-polymerase chain reaction (RT-qPCR). The correlation between the expression of exosomal miRNAs and the clinicopathological features of lung cancer was investigated. To assess the diagnostic efficacy of exosomal miRNAs for lung cancer, the receiver operating characteristic (ROC) curve analysis was conducted. The optimal cutoff value of exosomal miRNAs was determined in the testing cohort and subsequently confirmed in the validation cohort.

Results

The results showed that the expression of exosomal miR-1290 was significantly elevated, while that of miR-29c-3p was significantly decreased in the plasma of lung cancer patients, especially in those with early-stage lung cancer, compared to individuals with benign lung conditions (P < 0.01). Exosomal miR-1290 and miR-29c-3p demonstrated superior diagnostic efficacy compared to conventional tumor biomarkers in distinguishing between lung cancer and benign lung diseases, as evidenced by their respective area under the curve (AUC) values of 0.934 and 0.868. Furthermore, exosomal miR-1290 and miR-29c-3p exhibited higher diagnostic efficiency in early-stage lung cancer than traditional tumor markers, with AUC values of 0.947 and 0.895, respectively. Notably, both exosomal miR-1290 and miR-29c-3p displayed substantial discriminatory capacity in distinguishing between non-small cell lung cancer (NSCLC) and small cell lung cancer (SCLC), as indicated by their respective AUC values of 0.810 and 0.842.

Conclusions

The findings of this study provided evidence that exosomal miR-1290 and miR-29c-3p hold significant potential as biomarkers for the early detection of lung cancer, as well as for differentiating between NSCLC and SCLC.

An Overview of Systemic Targeted Therapy in Renal Cell Carcinoma, with a Focus on Metastatic Renal Cell Carcinoma and Brain Metastases

The most commonly diagnosed malignancy of the urinary system is represented by renal cell carcinoma. Various subvariants of RCC were described, with a clear-cell type prevailing in about 85% of all RCC tumors. Patients with metastases from renal cell carcinoma did not have many effective therapies until the end of the 1980s, as long as hormonal therapy and chemotherapy were the only options available. The outcomes were unsatisfactory due to the poor effectiveness of the available therapeutic options, but then interferon-alpha and interleukin-2 showed treatment effectiveness, providing benefits but only for less than half of the patients. However, it was not until 2004 that targeted therapies emerged, prolonging the survival rate. Currently, new technologies and strategies are being developed to improve the actual efficacy of available treatments and their prognostic aspects. This article summarizes the mechanisms of action, importance, benefits, adverse events of special interest, and efficacy of immunotherapy in metastatic renal cell carcinoma, with a focus on brain metastases.

Immune checkpoint inhibitors in EGFR-mutant non-small cell lung cancer: A systematic review

BACKGROUND

Since their first introduction in clinical practice, immune checkpoint inhibitors showed limited benefit in patients with NSCLC harboring EGFR mutations. With the rationale of increasing immune activation, combinatorial ICI strategies have been evaluated also in this subgroup of patients.

METHODS

We performed a systematic review on efficacy of ICI-based strategies in EGFR-mutant NSCLC according to most updated evidence.

RESULTS

Overall, ICI monotherapy and ICI plus chemotherapy confirm to be ineffective in EGFR-mutant NSCLC, whereas the combination of ICI with antiangiogenic and chemotherapy showed promising results. Limited data are available with alternative ICI combination strategies, driven by strong biological rationale of modulating the tumor immune microenvironment.

CONCLUSIONS

To date, the available evidence do not support the use of ICI in patients with NSCLC harboring EGFR mutations. Clinical trials are ongoing to define which is the best timing and exploring novel combinations with ICI in this specific disease.

Clinical and translational relevance of intratumor heterogeneity

Intratumor heterogeneity (ITH) is a driver of tumor evolution and a main cause of therapeutic resistance. Despite its importance, measures of ITH are still not incorporated into clinical practice. Consequently, standard treatment is frequently ineffective for patients with heterogeneous tumors as changes to treatment regimens are made only after recurrence and disease progression. More effective combination therapies require a mechanistic understanding of ITH and ways to assess it in clinical samples. The growth of technologies enabling the spatially intact analysis of tumors at the single-cell level and the development of sophisticated preclinical models give us hope that ITH will not simply be used as a predictor of a poor outcome but will guide treatment decisions from diagnosis through treatment.

Padlock Probe-Based Targeted In Situ Sequencing: Overview of Methods and Applications

Elucidating spatiotemporal changes in gene expression has been an essential goal in studies of health, development, and disease. In the emerging field of spatially resolved transcriptomics, gene expression profiles are acquired with the tissue architecture maintained, sometimes at cellular resolution. This has allowed for the development of spatial cell atlases, studies of cell-cell interactions, and in situ cell typing. In this review, we focus on padlock probe-based in situ sequencing, which is a targeted spatially resolved transcriptomic method. We summarize recent methodological and computational tool developments and discuss key applications. We also discuss compatibility with other methods and integration with multiomic platforms for future applications.

EGFR exon 20 insertion mutations and ERBB2 mutations in lung cancer: a narrative review on approved targeted therapies from oral kinase inhibitors to antibody-drug conjugates

Background and Objective

This review will provide an overview of EGFR and ERBB2 mutations in non-small-cell lung cancer (NSCLC) with a focus on recent clinical approvals.

Methods

We obtained data from the literature in accordance with narrative review reporting guidelines.

Key Content and Findings

EGFR mutations are present in up to 15-20% of all NSCLCs; amongst these, 10% correspond to kinase domain insertions in exon 20. Structurally similar, ERBB2 (HER2) mutations occurs in 1-4% of NSCLCs, mostly consisting of insertions or point mutations. The majority of EGFR exon 20 insertions occur within the loop following the regulatory C-helix and activate the kinase domain of EGFR without generating a therapeutic window to gefitinib, erlotinib, afatinib, dacomitinib or osimertinib. Mobocertinib represents a novel class of covalent EGFR inhibitors with a modest therapeutic window to these mutants and induces anti-tumor responses in a portion of patients [at 160 mg/day: response rate of <30% with duration of response (DoR) >17 months and progression-free survival (PFS) of >7 months] albeit with mucocutaneous and gastrointestinal toxicities. The bi-specific EGFR-MET antibody amivantamab-vmjw has modest but broad preclinical activity in EGFR-driven cancers and specifically for EGFR exon 20 insertion-mutated NSCLC has response rates <40% and PFS of <8.5 months at the cost of both infusion-related plus on-target toxicities. Both drugs were approved in 2021. The clinical development of kinase inhibitors for ERBB2-mutated NSCLC has been thwarted by mucocutaneous/gastrointestinal toxicities that preclude a pathway for drug approval, as the case of poziotinib. However, the activation of ERBB2 has allowed for repurposing of antibody-drug conjugates (ADCs) that target ERBB2 with cytotoxic payloads. The FDA approved fam-trastuzumab deruxtecan-nxki in 2022 for NSCLC based on response rate of >55%, DoR >9 months, PFS >8 months and manageable adverse events (including cytopenias, nausea and less commonly pneumonitis). Other therapies in clinical development include sunvozertinib and zipalertinib, among others. In addition, traditional cytotoxic chemotherapy has some activity in these tumors.

Conclusions

The approvals of mobocertinib, amivantamab, and trastuzumab deruxtecan represent the first examples of precision oncology for EGFR exon 20 insertion-mutated and ERBB2-mutated NSCLCs.

Methylated SEPT9 combined with AFP and PIVKA-II is effective for the detection of HCC in high-risk population

BACKGROUND

The methylation SEPT9 (mSEPT9) appeared to be effective for hepatocellular carcinoma (HCC) detection. However, its performance in high-risk population has not been validated. We designed a pilot study and aimed to investigate the performance of mSEPT9, AFP, PIVKA-II and their combination in hepatic cirrhosis (HC) population.

METHODS

A training cohort was established including 103 HCC and 114 HC patients. 10 ml blood was collected from each patient with K₂EDTA tubes, and 3-4 ml plasma was extracted for subsequent tests. The performance of mSEPT9, AFP, PIVKA-II and their combination was optimized by the training cohort. Test performance was prospectively validated with a validation cohort, including 51 HCC and 121 HC patients.

RESULTS

At the optimal thresholds in the training cohort, the sensitivity, specificity and area under curve (AUC) was 72.82%, 89.47%, 0.84, and 48.57%, 89.92%, 0.79, and 63.64%, 95.95%, 0.79 for mSEPT9, AFP and PIVKA-II, respectively. The combined test significantly increased the sensitivity to 84.47% (P < 0.05) at the specificity of 86.84% with an AUC of 0.91. Stage-dependent performance was observed with all single markers and their combination in plasma marker levels, positive detection rate (PDR) and AUC. Moderate correlation was found between mSEPT9 and AFP plasma levels (r = 0.527, P < 0.0001). Good complementarity was found between any two of the three markers, providing optimal sensitivity in HCC detection when used in combination. Subsequent validation achieved a sensitivity, specificity and AUC of 65.31%, 92.86%, 0.80, and 44.24%, 89.26%, 0.75, and 62.22%, 95.27%, 0.78 for mSEPT9, AFP and PIVKA-II, respectively. The combined test yielded a significantly increased sensitivity of 84.00% (P < 0.05) at 85.57% specificity, with an AUC at 0.89.

CONCLUSIONS

The performance was optimal by the combination of mSEPT9, AFP, PIVKA-II compared with any single marker, and the combination may be effective for HCC opportunistic screening in HC population.

Clinical trial designs for evaluating and exploiting cancer evolution

The evolution of drug-resistant cell subpopulations causes cancer treatment failure. Current preclinical evidence shows that it is possible to model herding of clonal evolution and collateral sensitivity where an initial treatment could favourably influence the response to a subsequent one. Novel therapy strategies exploiting this understanding are being considered, and clinical trial designs for steering cancer evolution are needed. Furthermore, preclinical evidence suggests that different subsets of drug-sensitive and resistant clones could compete between themselves for nutrients/blood supply, and clones that populate a tumour do so at the expense of other clones. Treatment paradigms based on this clinical application of exploiting cell-cell competition include intermittent dosing regimens or cycling different treatments before progression. This will require clinical trial designs different from the conventional practice of evaluating responses to individual therapy regimens. Next-generation sequencing to assess clonal dynamics longitudinally will improve current radiological assessment of clinical response/resistance and be incorporated into trials exploiting evolution. Furthermore, if understood, clonal evolution can be used to therapeutic advantage, improving patient outcomes based on a new generation of clinical trials.

Cellular barcoding: From developmental tracing to anti-tumor drug discovery

Clonal evolution has gained immense attention in explaining cancer cell status, history, and fate during cancer progression. Current single-cell or spatial transcriptome technologies have broadened our understanding of various mechanisms underlying cancer initiation, relapse, and drug resistance. However, technical challenges still hinder a better understanding of the dynamics of distinctive phenotypic states and abnormal trajectories from normal physiological transition to malignant stages. Cellular barcoding enabled lineage tracing on parallelly massive cells at single-cell resolution through different mechanisms lately, enabling new insights into exploring developmental trajectories, cancer progression, and targeted therapies. This review summarizes the latest noteworthy and robust strategies for different types of cellular barcodes. To introduce the major characteristics, advantages and limitations of these different strategies, this review will further guide in choosing or improving cellular barcoding technologies and their applications in cancer research.

New genetic and epigenetic insights into the chemokine system: the latest discoveries aiding progression toward precision medicine

Over the past thirty years, the importance of chemokines and their seven-transmembrane G protein-coupled receptors (GPCRs) has been increasingly recognized. Chemokine interactions with receptors trigger signaling pathway activity to form a network fundamental to diverse immune processes, including host homeostasis and responses to disease. Genetic and nongenetic regulation of both the expression and structure of chemokines and receptors conveys chemokine functional heterogeneity. Imbalances and defects in the system contribute to the pathogenesis of a variety of diseases, including cancer, immune and inflammatory diseases, and metabolic and neurological disorders, which render the system a focus of studies aiming to discover therapies and important biomarkers. The integrated view of chemokine biology underpinning divergence and plasticity has provided insights into immune dysfunction in disease states, including, among others, coronavirus disease 2019 (COVID-19). In this review, by reporting the latest advances in chemokine biology and results from analyses of a plethora of sequencing-based datasets, we outline recent advances in the understanding of the genetic variations and nongenetic heterogeneity of chemokines and receptors and provide an updated view of their contribution to the pathophysiological network, focusing on chemokine-mediated inflammation and cancer. Clarification of the molecular basis of dynamic chemokine-receptor interactions will help advance the understanding of chemokine biology to achieve precision medicine application in the clinic.

MGME1 associates with poor prognosis and is vital for cell proliferation in lower-grade glioma

OBJECTIVE

Mitochondrial genome maintenance exonuclease 1 (MGME1) is associated with DNA depletion, deletion, duplication, and rearrangement. However, the function of MGME1 in tumors, especially lower-grade gliomas (LGGs), has not been established.

METHODS

Pan-cancer analysis was used to define the expression patterns and prognostic value of MGME1 in various cancers. Subsequently, we systematically determined the associations between MGME1 expression and clinicopathological characteristics, prognosis, biological functions, immune characteristics, genomic mutations, and therapeutic responses of LGGs based on their expression patterns. The expression level and specific functions of MGME1 in LGGs was detected by conducting in vitro experiments.

RESULTS

Abnormally enhanced and high MGME1 expressions were associated with poor prognoses of various tumors, including LGG. Multivariate and univariate Cox regression analyses manifested that MGME1 expression was an independent prognostic biomarker for LGG. The immune-related signatures, infiltration of immune cells, immune checkpoint genes (ICPGs), copy number alteration (CNA), tumor mutation burden (TMB), and treatment responses of LGG patients were associated with the expression of MGME1. The in vitro experiments affirmed that MGME1 was elevated and tightly connected with the cell proliferation and cell cycle in LGG.

CONCLUSIONS

MGME1 is an independent prognostic biomarker and closely related to the cell proliferation in LGG.

Lymphocyte networks are dynamic cellular communities in the immunoregulatory landscape of lung adenocarcinoma

Lymphocytes are key for immune surveillance of tumors, but our understanding of the spatial organization and physical interactions that facilitate lymphocyte anti-cancer functions is limited. We used multiplexed imaging, quantitative spatial analysis, and machine learning to create high-definition maps of lung tumors from a Kras/Trp53-mutant mouse model and human resections. Networks of interacting lymphocytes ("lymphonets") emerged as a distinctive feature of the anti-cancer immune response. Lymphonets nucleated from small T cell clusters and incorporated B cells with increasing size. CXCR3-mediated trafficking modulated lymphonet size and number, but T cell antigen expression directed intratumoral localization. Lymphonets preferentially harbored TCF1+ PD-1+ progenitor CD8+ T cells involved in responses to immune checkpoint blockade (ICB) therapy. Upon treatment of mice with ICB or an antigen-targeted vaccine, lymphonets retained progenitor and gained cytotoxic CD8+ T cell populations, likely via progenitor differentiation. These data show that lymphonets create a spatial environment supportive of CD8+ T cell anti-tumor responses.

ACT-Discover: identifying karyotype heterogeneity in pancreatic cancer evolution using ctDNA

BACKGROUND

Liquid biopsies and the dynamic tracking of somatic mutations within circulating tumour DNA (ctDNA) can provide insight into the dynamics of cancer evolution and the intra-tumour heterogeneity that fuels treatment resistance. However, identifying and tracking dynamic changes in somatic copy number alterations (SCNAs), which have been associated with poor outcome and metastasis, using ctDNA is challenging. Pancreatic adenocarcinoma is a disease which has been considered to harbour early punctuated events in its evolution, leading to an early fitness peak, with minimal further subclonal evolution.

METHODS

To interrogate the role of SCNAs in pancreatic adenocarcinoma cancer evolution, we applied whole-exome sequencing of 55 longitudinal cell-free DNA (cfDNA) samples taken from 24 patients (including 8 from whom a patient-derived xenograft (PDX) was derived) with metastatic disease prospectively recruited into a clinical trial. We developed a method, Aneuploidy in Circulating Tumour DNA (ACT-Discover), that leverages haplotype phasing of paired tumour biopsies or PDXs to identify SCNAs in cfDNA with greater sensitivity.

RESULTS

SCNAs were observed within 28 of 47 evaluable cfDNA samples. Of these events, 30% could only be identified by harnessing the haplotype-aware approach leveraged in ACT-Discover. The exceptional purity of PDX tumours enabled near-complete phasing of genomic regions in allelic imbalance, highlighting an important auxiliary function of PDXs. Finally, although the classical model of pancreatic cancer evolution emphasises the importance of early, homogenous somatic events as a key requirement for cancer development, ACT-Discover identified substantial heterogeneity of SCNAs, including parallel focal and arm-level events, affecting different parental alleles within individual tumours. Indeed, ongoing acquisition of SCNAs was identified within tumours throughout the disease course, including within an untreated metastatic tumour.

CONCLUSIONS

This work demonstrates the power of haplotype phasing to study genomic variation in cfDNA samples and reveals undiscovered intra-tumour heterogeneity with important scientific and clinical implications. Implementation of ACT-Discover could lead to important insights from existing cohorts or underpin future prospective studies seeking to characterise the landscape of tumour evolution through liquid biopsy.

Synergistic effects of combined immunotherapy strategies in a model of multifocal hepatocellular carcinoma

Immune checkpoint-inhibitor combinations are the best therapeutic option for advanced hepatocellular carcinoma (HCC) patients, but improvements in efficacy are needed to improve response rates. We develop a multifocal HCC model to test immunotherapies by introducing c-myc using hydrodynamic gene transfer along with CRISPR-Cas9-mediated disruption of p53 in mouse hepatocytes. Additionally, induced co-expression of luciferase, EGFP, and the melanosomal antigen gp100 facilitates studies on the underlying immunological mechanisms. We show that treatment of the mice with a combination of anti-CTLA-4 + anti-PD1 mAbs results in partial clearance of the tumor with an improvement in survival. However, the addition of either recombinant IL-2 or an anti-CD137 mAb markedly improves both outcomes in these mice. Combining tumor-specific adoptive T cell therapy to the aCTLA-4/aPD1/rIL2 or aCTLA-4/aPD1/aCD137 regimens enhances efficacy in a synergistic manner. As shown by multiplex tissue immunofluorescence and intravital microscopy, combined immunotherapy treatments enhance T cell infiltration and the intratumoral performance of T lymphocytes.

Antibodies against endogenous retroviruses promote lung cancer immunotherapy

B cells are frequently found in the margins of solid tumours as organized follicles in ectopic lymphoid organs called tertiary lymphoid structures (TLS)1,2. Although TLS have been found to correlate with improved patient survival and response to immune checkpoint blockade (ICB), the underlying mechanisms of this association remain elusive1,2. Here we investigate lung-resident B cell responses in patients from the TRACERx 421 (Tracking Non-Small-Cell Lung Cancer Evolution Through Therapy) and other lung cancer cohorts, and in a recently established immunogenic mouse model for lung adenocarcinoma3. We find that both human and mouse lung adenocarcinomas elicit local germinal centre responses and tumour-binding antibodies, and further identify endogenous retrovirus (ERV) envelope glycoproteins as a dominant anti-tumour antibody target. ERV-targeting B cell responses are amplified by ICB in both humans and mice, and by targeted inhibition of KRAS(G12C) in the mouse model. ERV-reactive antibodies exert anti-tumour activity that extends survival in the mouse model, and ERV expression predicts the outcome of ICB in human lung adenocarcinoma. Finally, we find that effective immunotherapy in the mouse model requires CXCL13-dependent TLS formation. Conversely, therapeutic CXCL13 treatment potentiates anti-tumour immunity and synergizes with ICB. Our findings provide a possible mechanistic basis for the association of TLS with immunotherapy response.

The evolution of non-small cell lung cancer metastases in TRACERx

Metastatic disease is responsible for the majority of cancer-related deaths1. We report the longitudinal evolutionary analysis of 126 non-small cell lung cancer (NSCLC) tumours from 421 prospectively recruited patients in TRACERx who developed metastatic disease, compared with a control cohort of 144 non-metastatic tumours. In 25% of cases, metastases diverged early, before the last clonal sweep in the primary tumour, and early divergence was enriched for patients who were smokers at the time of initial diagnosis. Simulations suggested that early metastatic divergence more frequently occurred at smaller tumour diameters (less than 8 mm). Single-region primary tumour sampling resulted in 83% of late divergence cases being misclassified as early, highlighting the importance of extensive primary tumour sampling. Polyclonal dissemination, which was associated with extrathoracic disease recurrence, was found in 32% of cases. Primary lymph node disease contributed to metastatic relapse in less than 20% of cases, representing a hallmark of metastatic potential rather than a route to subsequent recurrences/disease progression. Metastasis-seeding subclones exhibited subclonal expansions within primary tumours, probably reflecting positive selection. Our findings highlight the importance of selection in metastatic clone evolution within untreated primary tumours, the distinction between monoclonal versus polyclonal seeding in dictating site of recurrence, the limitations of current radiological screening approaches for early diverging tumours and the need to develop strategies to target metastasis-seeding subclones before relapse.

Genomic-transcriptomic evolution in lung cancer and metastasis

Intratumour heterogeneity (ITH) fuels lung cancer evolution, which leads to immune evasion and resistance to therapy1. Here, using paired whole-exome and RNA sequencing data, we investigate intratumour transcriptomic diversity in 354 non-small cell lung cancer tumours from 347 out of the first 421 patients prospectively recruited into the TRACERx study2,3. Analyses of 947 tumour regions, representing both primary and metastatic disease, alongside 96 tumour-adjacent normal tissue samples implicate the transcriptome as a major source of phenotypic variation. Gene expression levels and ITH relate to patterns of positive and negative selection during tumour evolution. We observe frequent copy number-independent allele-specific expression that is linked to epigenomic dysfunction. Allele-specific expression can also result in genomic-transcriptomic parallel evolution, which converges on cancer gene disruption. We extract signatures of RNA single-base substitutions and link their aetiology to the activity of the RNA-editing enzymes ADAR and APOBEC3A, thereby revealing otherwise undetected ongoing APOBEC activity in tumours. Characterizing the transcriptomes of primary-metastatic tumour pairs, we combine multiple machine-learning approaches that leverage genomic and transcriptomic variables to link metastasis-seeding potential to the evolutionary context of mutations and increased proliferation within primary tumour regions. These results highlight the interplay between the genome and transcriptome in influencing ITH, lung cancer evolution and metastasis.

A multispecies framework for modeling adaptive immunity and immunotherapy in cancer

Predator-prey theory is commonly used to describe tumor growth in the presence of selective pressure from the adaptive immune system. These interactions are mediated by the tumor immunopeptidome (what the tumor "shows" the body) and the T-cell receptor (TCR) repertoire (how well the body "sees" cancer cells). The tumor immunopeptidome comprises neoantigens which can be gained and lost throughout tumorigenesis and treatment. Heterogeneity in the immunopeptidome is predictive of poor response to immunotherapy in some tumor types, suggesting that the TCR repertoire is unable to support a fully polyclonal response against every neoantigen. Importantly, while tumor and T-cell populations are known to compete with each other for intratumoral resources, whether between-lineage competition among peripheral T cells influences the TCR repertoire is unknown and difficult to interrogate experimentally. Computational models may offer a way to investigate these phenomena and deepen our understanding of the tumor-immune axis. Here, we construct a predator-prey-like model and calibrate it to preclinical and clinical data to describe tumor growth and immunopeptidome diversification. Simultaneously, we model the expansion of antigen-specific T-cell lineages and their consumption of both lineage-specific antigenic resources and lineage-agnostic, shared resources. This predator-prey-like framework accurately described clinically observed immunopeptidomes; recapitulated response-associated effects of immunotherapy, including immunoediting; and allowed exploration of treatment of tumors with varying growth and mutation rates.

Longitudinal ctDNA profiling in precision oncology and immunο-oncology

Serial analysis of circulating tumor DNA (ctDNA) over the disease course is emerging as a prognostic, predictive and patient-monitoring biomarker. In the metastatic setting, several multigene ctDNA assays have been approved or recommended by regulatory organizations for personalized targeted therapy, especially for lung cancer. By contrast, in nonmetastatic disease, detection of ctDNA resulting from minimal residual disease (MRD) following multimodal treatment with curative intent presents major technical challenges. Several studies using tumor genotyping-informed serial ctDNA profiling have provided promising findings on the sensitivity and specificity of ctDNA in predicting the risk of recurrence. We discuss progress, limitations and future perspectives relating to the use of ctDNA as a biomarker to guide targeted therapy in metastatic disease, as well as the use of ctDNA MRD detection to guide adjuvant treatment in the nonmetastatic setting.

Navigating the liquid biopsy Minimal Residual Disease (MRD) in non-small cell lung cancer: Making the invisible visible

Liquid biopsy has gained increasing interest in the growing era of precision medicine as minimally invasive technique. Recent findings demonstrated that detecting minimal or molecular residual disease (MRD) in NSCLC is a challenging matter of debate that need multidisciplinary competencies, avoiding the overtreatment risk along with achieving a significant survival improvement. This review aims to provide practical consideration for solving data interpretation questions about MRD in NSCLC thanks to the close cooperation between biologists and oncology clinicians. We discussed with a translational approach the critical point of view from benchside, bedside and bunchside to facilitate the future applicability of liquid biopsy in this setting. Herein, we defined the clinical significance of MRD, focusing on relevant practical consideration about advantages and disadvantages, speculating on future clinical trial design and standardization of MRD technology.

Evolvability and emergence of tumor heterogeneity as a space-time function

The loss of control of cell proliferation, apoptosis regulation and contact inhibition leads to tumor development. While benign tumors are restricted to their primary space, i.e. where these tumors first originate, the metastatic tumors not only disseminate- facilitated by hypoxia-driven neovascularization- to distant secondary sites but also show substantial changes in metabolism, tissue architectures, gene expression profiles and immune phenotypes. All these alterations result in radio-, chemo- and immune-resistance rendering these metastatic tumor cells refractory to therapy. Since the beginning of the transformation, these factors- which influence each other- are incorporated to the developing and metastasizing tumor. As a result, the complexities in the heterogeneity of tumor progressively increase. This space-time function in the heterogeneity of tumors is generated by various conditions and factors at the genetic as well as microenvironmental levels, for example, endogenous retroviruses, methylation and epigenetic dysregulation that may be etiology-specific, cancer associated inflammation, remodeling of the extracellular matrix and mesenchymal cell shifted functions. On the one hand, these factors may cause de-differentiation of the tumor cells leading to cancer stem cells that contribute to radio-, chemo- and immune-resistance and recurrence of tumors. On the other hand, they may also enhance the heterogeneity under specific microenvironment-driven proliferation. In this editorial, we intend to underline the importance of heterogeneity in cancer progress, its evaluation and its use in correlation with the tumor evolution in a specific patient as a field of research for achieving precise patient-tailored treatments and amelioration of diagnostic (monitoring) tools and prognostic capacity.

The coming decade in precision oncology: six riddles

High-throughput methods to investigate tumour omic landscapes have quickly catapulted cancer specialists into the precision oncology era. The singular lesson of precision oncology might be that, for it to be precise, treatment must be personalized, as each cancer's complex molecular and immune landscape differs from patient to patient. Transformative therapies include those that are targeted at the sequelae of molecular abnormalities or at immune mechanisms, and, increasingly, pathways previously thought to be undruggable have become druggable. Critical to applying precision medicine is the concept that the right combination of drugs must be chosen for each patient and used at the right stage of the disease. Multiple puzzles remain that complicate therapy choice, including evidence that deleterious mutations are common in normal tissues and non-malignant conditions. The host's role is also likely to be key in determining treatment response, especially for immunotherapy. Indeed, maximizing the impact of immunotherapy will require omic analyses to match the right immune-targeted drugs to the individualized patient and tumour setting. In this Perspective, we discuss six key riddles that must be solved to optimize the application of precision oncology to otherwise lethal malignancies.

TRB CDR3-cancer testis antigen chemical complementarity scoring for identifying productive immune responses in renal cell carcinoma

BACKGROUND

Immunogenomics approaches to the characterization of renal cell carcinoma (RCC) have helped to better our understanding of the features of RCC immune dysfunction. However, much is still unknown with regard to specific immune interactions and their impact in the tumor microenvironment.

OBJECTIVE

This study applied chemical complementarity scoring for the TRB complementarity determining region-3 (CDR3) amino acid sequences and cancer testis antigens (CTAs) to determine whether such complementarity correlated with survival and the expression of immune marker genes.

METHODS

TRB recombination reads from RCC tumor samples from RNAseq files obtained from two separate databases, Moffitt Cancer Center and The Cancer Genome Atlas (TCGA), were evaluated. Chemical complementarity scores (CSs) were calculated for TRB CDR3-CTA pairs and survival assessments based on those CSs were performed.

RESULTS

Moffitt Cancer Center and TCGA cases representing the upper 50th percentile of chemical CSs for TRB CDR3 amino acid sequences and the CTA POTEA were found to be associated with a better overall survival (OS) Also, greater tumor RNA expression of multiple immune signature genes, including granzyme A, granzyme B, and interferon-gamma were correlated with the higher chemical CSs.

CONCLUSIONS

These results indicate that TRB CDR3-CTA chemical complementarity scoring may be useful in distinguishing RCC cases with a productive, anti-tumor immune response from cases where basic immune parameter assessments are inconsistent with a productive immune response.

The Role of Cell-Free DNA in Cancer Treatment Decision Making

The aim of this review is to evaluate the present status of the use of cell-free DNA and its fraction of circulating tumor DNA (ctDNA) because this year July 2022, an ESMO guideline was published regarding the application of ctDNA in patient care. This review is for clinical oncologists to explain the concept, the terms used, the pros and cons of ctDNA; thus, the technical aspects of the different platforms are not reviewed in detail, but we try to help in navigating the current knowledge in liquid biopsy. Since the validated and adequately sensitive ctDNA assays have utility in identifying actionable mutations to direct targeted therapy, ctDNA may be used for this soon in routine clinical practice and in other different areas as well. The cfDNA fragments can be obtained by liquid biopsy and can be used for diagnosis, prognosis, and selecting among treatment options in cancer patients. A great proportion of cfDNA comes from normal cells of the body or from food uptake. Only a small part (<1%) of it is related to tumors, originating from primary tumors, metastatic sites, or circulating tumor cells (CTCs). Soon the data obtained from ctDNA may routinely be used for finding minimal residual disease, detecting relapse, and determining the sites of metastases. It might also be used for deciding appropriate therapy, and/or emerging resistance to the therapy and the data analysis of ctDNA may be combined with imaging or other markers. However, to achieve this goal, further clinical validations are inevitable. As a result, clinicians should be aware of the limitations of the assays. Of course, several open questions are still under research and because of it cfDNA and ctDNA testing are not part of routine care yet.

Non-Small Cell Lung Cancer (NSCLC) in Young Adults, Age < 50, Is Associated with Late Stage at Presentation and a Very Poor Prognosis in Patients That Do Not Have a Targeted Therapy Option: A Real-World Study

(1) Background: Non-small cell lung cancer (NSCLC) in young patients is uncommon. Real-world evidence on the outcomes of these patients is limited. (2) Methods: We conducted a retrospective cohort study of young NSCLC patients, age < 50 years at diagnosis, who were treated between 2011−2020 in South-East-London cancer centres. Clinicopathological characteristics, treatment and outcomes were analysed. (3) Results: Of 248 NSCLC patients, median age was 46 years, 50% (n = 125) female, 58% (n = 145) white, 18% (n = 45) black and 4% (n = 10) Asian ethnicity. Amongst patients with a documented smoking history, 30% (n = 64) were never-smokers. Most patients had adenocarcinoma (77%, n = 191) and presented with metastatic disease (67%, n = 166). Only 31% (n = 76) had treatment with curative intent. In patients who presented or developed metastatic non-squamous NSCLC (n = 179), EGFR mutation status was known in 88% (n = 157) and mutation present in 19% (n = 34), ALK was known in 66% (n = 118) with a translocation in 10% (n = 18), ROS1 status was known in 57% (n = 102) with a translocation in 4% (n = 8), and KRAS status was known in 66% (n = 119) with a mutation in 12% (n = 22). Overall, 76% (n = 152) patients with metastatic NSCLC received first-line systemic anti-cancer therapy. Median overall survival in metastatic NSCLC was 9.0 months (95% CI 6.5−11.6 months), with superior median overall survival in those with a targeted therapy option (28.7 months) compared to those without (6.6 months; p < 0.001). (4) Conclusion: Young patients contribute a significant proportion of those presenting with lung cancer. They present with advanced stage at diagnosis and have a poor prognosis. Identification of a targeted therapy option is associated with improved survival. However, most patients do not have a known genomic driver, which is in part due to limited testing, particularly in the early years of this study period. These findings highlight the particular importance of rapid-turnaround comprehensive genomic profiling in this age group and the need to identify strategies to facilitate earlier diagnosis in young NSCLC patients.