Targeting KRAS in Lung Cancer Beyond KRAS G12C Inhibitors: The Immune Regulatory Role of KRAS and Novel Therapeutic Strategies

Approximately 20% of lung adenocarcinomas harbor KRAS mutations, an oncogene that drives tumorigenesis and has the ability to alter the immune system and the tumor immune microenvironment. While KRAS was considered “undruggable” for decades, specific KRAS G12C covalent inhibitors have recently emerged, although their promising results are limited to a subset of patients. Several other drugs targeting KRAS activation and downstream signaling pathways are currently under investigation in early-phase clinical trials. In addition, KRAS mutations can co-exist with other mutations in significant genes in cancer (e.g., STK11 and KEAP1) which induces tumor heterogeneity and promotes different responses to therapies. This review describes the molecular characterization of KRAS mutant lung cancers from a biologic perspective to its clinical implications. We aim to summarize the tumor heterogeneity of KRAS mutant lung cancers and its immune-regulatory role, to report the efficacy achieved with current immunotherapies, and to overview the therapeutic approaches targeting KRAS mutations besides KRAS G12C inhibitors.

Patient-derived xenograft models capture genomic heterogeneity in endometrial cancer

Background Endometrial cancer (EC) is a major gynecological cancer with increasing incidence. It comprises four molecular subtypes with differing etiology, prognoses, and responses to chemotherapy. In the future, clinical trials testing new single agents or combination therapies will be targeted to the molecular subtype most likely to respond. As pre-clinical models that faithfully represent the molecular subtypes of EC are urgently needed, we sought to develop and characterize a panel of novel EC patient-derived xenograft (PDX) models. Methods Here, we report whole exome or whole genome sequencing of 11 PDX models and their matched primary tumor. Analysis of multiple PDX lineages and passages was performed to study tumor heterogeneity across lineages and/or passages. Based on recent reports of frequent defects in the homologous recombination (HR) pathway in EC, we assessed mutational signatures and HR deficiency scores and correlated these with in vivo responses to the PARP inhibitor (PARPi) talazoparib in six PDXs representing the copy number high/p53-mutant and mismatch-repair deficient molecular subtypes of EC. Results PDX models were successfully generated from grade 2/3 tumors, including three uterine carcinosarcomas. The models showed similar histomorphology to the primary tumors and represented all four molecular subtypes of EC, including five mismatch-repair deficient models. The different PDX lineages showed a wide range of inter-tumor and intra-tumor heterogeneity. However, for most PDX models, one arm recapitulated the molecular landscape of the primary tumor without major genomic drift. An in vivo response to talazoparib was detected in four copy number high models. Two models (carcinosarcomas) showed a response consistent with stable disease and two models (one copy number high serous EC and another carcinosarcoma) showed significant tumor growth inhibition, albeit one consistent with progressive disease; however, all lacked the HR deficiency genomic signature. Conclusions EC PDX models represent the four molecular subtypes of disease and can capture intra-tumor heterogeneity of the original primary tumor. PDXs of the copy number high molecular subtype showed sensitivity to PARPi; however, deeper and more durable responses will likely require combination of PARPi with other agents.

3D APT and NOE CEST-MRI of healthy volunteers and patients with non-enhancing glioma at 3 T

Objective Clinical application of chemical exchange saturation transfer (CEST) can be performed with investigation of amide proton transfer (APT) and nuclear Overhauser enhancement (NOE) effects. Here, we investigated APT- and NOE-weighted imaging based on advanced CEST metrics to map tumor heterogeneity of non-enhancing glioma at 3 T. Materials and methods APT- and NOE-weighted maps based on Lorentzian difference (LD) and inverse magnetization transfer ratio (MTRREX) were acquired with a 3D snapshot CEST acquisition at 3 T. Saturation power was investigated first by varying B1 (0.5–2 µT) in 5 healthy volunteers then by applying B1 of 0.5 and 1.5 µT in 10 patients with non-enhancing glioma. Tissue contrast (TC) and contrast-to-noise ratios (CNR) were calculated between glioma and normal appearing white matter (NAWM) and grey matter, in APT- and NOE-weighted images. Volume percentages of the tumor showing hypo/hyperintensity (VPhypo/hyper,CEST) in APT/NOE-weighted images were calculated for each patient. Results LD APT resulting from using a B1 of 1.5 µT was found to provide significant positive TCtumor,NAWM and MTRREX NOE (B1 of 1.5 µT) provided significant negative TCtumor,NAWM in tissue differentiation. MTRREX-based NOE imaging under 1.5 µT provided significantly larger VPhypo,CEST than MTRREX APT under 1.5 µT. Conclusion This work showed that with a rapid CEST acquisition using a B1 saturation power of 1.5 µT and covering the whole tumor, analysis of both LD APT and MTRREX NOE allows for observing tumor heterogeneity, which will be beneficial in future studies using CEST-MRI to improve imaging diagnostics for non-enhancing glioma.

Multi-parametric PET/MRI With FDG and RGD for Enhanced Tumor Characterization of Patients With Cervical Cancer

Aim: The concept of personalized medicine has brought increased awareness to the importance of inter- and intra-tumor heterogeneity for cancer treatment. The aim of this study was to explore simultaneous multi-parametric PET/MRI prior to chemoradiotherapy for cervical cancer for characterization of tumors and tumor heterogeneity. Methods: Ten patients with histologically proven primary cervical cancer were examined with multi-parametric 68Ga-NODAGA-E[c(RGDyK)]2-PET/MRI for radiation treatment planning after diagnostic 18F-FDG-PET/CT. Standardized uptake values (SUV) of RGD and FDG, diffusion weighted MRI and the derived apparent diffusion coefficient (ADC), and pharmacokinetic maps obtained from dynamic contrast-enhanced MRI with the Tofts model (iAUC60, Ktrans, ve, and kep) were included in the analysis. The spatial relation between functional imaging parameters in tumors was examined by a correlation analysis and joint histograms at the voxel level. The ability of multi-parametric imaging to identify tumor tissue classes was explored using an unsupervised 3D Gaussian mixture model-based cluster analysis.Results: Functional MRI and PET of cervical cancers appeared heterogeneous both between patients and spatially within the tumors, and the relations between parameters varied strongly within the patient cohort. The strongest spatial correlation was observed between FDG uptake and ADC (median r=-0.7). There was moderate voxel-wise correlation between RGD and FDG uptake, and weak correlations between all other modalities. Distinct relations between the ADC and RGD uptake as well as the ADC and FDG uptake were apparent in joint histograms. A cluster analysis using the combination of ADC, FDG and RGD uptake suggested tissue classes which could potentially relate to tumor sub-volumes. Conclusion: A multi-parametric PET/MRI examination of patients with cervical cancer integrated with treatment planning and including estimation of angiogenesis and glucose metabolism as well as MRI diffusion and perfusion parameters is feasible. A combined analysis of functional imaging parameters indicates a potential of multi-parametric PET/MRI to contribute to a better characterization of tumor heterogeneity than the modalities alone. However, the study is based on small patient numbers and further studies are needed prior to the future design of individually adapted treatment approaches based on multi-parametric functional imaging.

Circadian Regulation Patterns With Distinct Immune Landscapes in Gliomas Aid in the Development of a Risk Model to Predict Prognosis and Therapeutic Response

Circadian disruption in tumorigenesis has been extensively studied, but how circadian rhythm (CR) affects the formation of tumor microenvironment (TME) and the crosstalk between TME and cancer cells is largely unknown, especially in gliomas. Herein, we retrospectively analyzed transcriptome data and clinical parameters of glioma patients from public databases to explore circadian rhythm-controlled tumor heterogeneity and characteristics of TME in gliomas. Firstly, we pioneered the construction of a CR gene set collated from five datasets and review literatures. Unsupervised clustering was used to identify two CR clusters with different CR patterns on the basis of the expression of CR genes. Remarkably, the CR cluster-B was characterized by enriched myeloid cells and activated immune-related pathways. Next, we applied principal component analysis to construct a CRscore to quantify CR patterns of individual tumors, and the function of the CRscore in prognostic prediction was further verified by univariate and multivariate regression analyses in combination with a nomogram. The CRscore could not only be an independent factor to predict prognosis of glioma patients but also guide patients to choose suitable treatment strategies: immunotherapy or chemotherapy. A glioma patient with a high CRscore might respond to immune checkpoint blockade, whereas one with a low CRscore could benefit from chemotherapy. In this study, we revealed that circadian rhythms modulated tumor heterogeneity, TME diversity, and complexity in gliomas. Evaluating the CRscore of an individual tumor would contribute to gaining a greater understanding of the tumor immune status of each patient, enhancing the accuracy of prognostic prediction, and suggesting more effective treatment options.

How Lineage Tracing Studies Can Unveil Tumor Heterogeneity in Breast Cancer

Lineage tracing studies have become a well-suited approach to reveal cellular hierarchies and tumor heterogeneity. Cellular heterogeneity, particularly in breast cancer, is still one of the main concerns regarding tumor progression and resistance to anti-cancer therapies. Here, we review the current knowledge about lineage tracing analyses that have contributed to an improved comprehension of the complexity of mammary tumors, highlighting how targeting different mammary epithelial cells and tracing their progeny can be useful to explore the intra- and inter-heterogeneity observed in breast cancer. In addition, we examine the strategies used to identify the cell of origin in different breast cancer subtypes and summarize how cellular plasticity plays an important role during tumorigenesis. Finally, we evaluate the clinical implications of lineage tracing studies and the challenges remaining to address tumor heterogeneity in breast cancer.

The transcriptional hallmarks of intra-tumor heterogeneity across a thousand tumors

Each tumor contains malignant cells that differ in genotype, phenotype, and in their interactions with the tumor micro-environment (TME). This results in distinct integrated cellular states that govern intra-tumor heterogeneity (ITH), a central challenge of cancer therapeutics. Dozens of recent studies have begun to describe ITH by single cell RNA-seq, but each study typically profiledonly a small number of tumors and provided a narrow view of transcriptional ITH. Here, we curate, annotate and integrate the data from 77 different studies to reveal the patterns of ITH across 1,163 tumor samples covering 24 tumor types. Focusing on the malignant cells, we find thousands of transcriptional ITH programs that can be described by 41 consensus meta-programs (MPs), each consisting of dozens of genes that are coordinately upregulated in subpopulations of cells within many different tumors. The MPs cover diverse cellular processes and differ in their cancer-type distribution. General MPs associated with processes such as cell cycle and stress vary within most tumors, while context-specific MPs reflect the unique biology of particular cancer types, often resembling developmental cell types and suggesting the co-existence of variable differentiation states within tumors. Some of the MPs are further associated with overall tumor proliferation or immune state, highlighting their potential clinical significance. Based on functional similarities among MPs, we propose a set of 11 hallmarks that together account for the majority of observed ITH programs. Given the breadth and scope of the investigated cohort, the MPs and hallmarks described here reflect the first comprehensive pan-cancer description of transcriptional ITH.