bims-preonc 2024-09-08 papers

bims-preonc

Biomed News

on Precision oncology

Issue of 2024–09–08
nine papers selected by
Ankita Daiya, OneCell Diagnostics Inc.

A Comprehensive Review of Bioinformatics Tools for Genomic Biomarker Discovery Driving Precision Oncology.
Personalized Therapy Selection by Integration of Molecular Cancer Classification by the 92-Gene Assay and Tumor Profiling in Patients With Cancer of Unknown Primary.
Biomarkers for Personalized Neoadjuvant Therapy in Triple-Negative Breast Cancer: Moving Forward.
Molecular biology as a driver in therapeutic choices for ovarian cancer.
Precision oncology across the ages: Impact on children, adolescents, and young adults.
Immunotherapy in Gastrointestinal Cancers.
Cost-effectiveness analysis of osimertinib plus chemotherapy for patients with EGFR-mutated advanced non-small cell lung cancer.
A multimodal neural network with gradient blending improves predictions of survival and metastasis in sarcoma.
Genomic Landscape of Pancreatic Neuroendocrine Tumors and Implications for Clinical Practice.

Genes (Basel). 2024 Aug 06. pii: 1036. [Epub ahead of print]15(8):

A Comprehensive Review of Bioinformatics Tools for Genomic Biomarker Discovery Driving Precision Oncology.

Alexis J Clark, James W Lillard.

  The rapid advancement of high-throughput technologies, particularly next-generation sequencing (NGS), has revolutionized cancer research by enabling the investigation of genetic variations such as SNPs, copy number variations, gene expression, and protein levels. These technologies have elevated the significance of precision oncology, creating a demand for biomarker identification and validation. This review explores the complex interplay of oncology, cancer biology, and bioinformatics tools, highlighting the challenges in statistical learning, experimental validation, data processing, and quality control that underpin this transformative field. This review outlines the methodologies and applications of bioinformatics tools in cancer genomics research, encompassing tools for data structuring, pathway analysis, network analysis, tools for analyzing biomarker signatures, somatic variant interpretation, genomic data analysis, and visualization tools. Open-source tools and repositories like The Cancer Genome Atlas (TCGA), Genomic Data Commons (GDC), cBioPortal, UCSC Genome Browser, Array Express, and Gene Expression Omnibus (GEO) have emerged to streamline cancer omics data analysis. Bioinformatics has significantly impacted cancer research, uncovering novel biomarkers, driver mutations, oncogenic pathways, and therapeutic targets. Integrating multi-omics data, network analysis, and advanced ML will be pivotal in future biomarker discovery and patient prognosis prediction.

Keywords:  RNA-Seq; bioinformatics; biomarker discovery; oncology; predictive algorithms

DOI:  https://doi.org/10.3390/genes15081036
JCO Precis Oncol. 2024 Sep;8 e2400191

Personalized Therapy Selection by Integration of Molecular Cancer Classification by the 92-Gene Assay and Tumor Profiling in Patients With Cancer of Unknown Primary.

Harry E Fuentes Bayne, Pashtoon M Kasi, Li Ma, Lowell L Hart, Jenna Wong, David R Spigel, Catherine A Schnabel, James A Reeves, Thorvardur R Halfdanarson, Kai Treuner, F Anthony Greco.

PURPOSE: Cancer of unknown primary (CUP) is a syndrome comprising metastatic cancers without a clinically identified primary site. Although patients with CUP have an unfavorable prognosis, treatment with site-specific therapies guided by clinical features, standard pathology, and molecular assays can improve overall survival. The 92-gene assay (CancerTYPE ID) is a gene expression-based classifier that helps identify the tissue of origin for metastatic cancers with unknown or uncertain diagnoses. This study reports the frequency of selected molecular aberrations of oncogenes, including KRAS, IDH1/2, BRCA1/2, and BRAF, in patients with CUP in the MOSAIC database to highlight potential treatment options.
METHODS: MOSAIC is a database of patients with CUP submitted for CancerTYPE ID testing and NeoTYPE biomarker testing. Tumor biopsy samples were analyzed by CancerTYPE ID for tumor type identification and further tested for molecular aberrations of oncogenes, including KRAS, IDH1/2, BRCA1/2, and BRAF.
RESULTS: CancerTYPE ID identified a specific tumor type in 92.5% (2,929 of 3,168) of CUP cases in the MOSAIC database. The most commonly identified histological type was adenocarcinoma (75.4%), with pancreaticobiliary being the most common molecularly diagnosed cancer (24.9%). Aberrations in KRAS, IDH1/2, BRCA, and BRAF genes were identified in 18.8% (n = 597) of biopsies. A cancer-specific US Food and Drug Administration (FDA)-approved or investigational targeted therapy was potentially available for 24.6% (n = 147) of these patients.
CONCLUSION: This retrospective analysis supports incorporating CancerTYPE ID into the evaluation for patients with CUP to help determine the tissue of origin and identify actionable genetic alterations. This approach may allow more patients with CUP to benefit from site-specific FDA-approved targeted therapies or enrollment into clinical trials.

DOI: https://doi.org/10.1200/PO.24.00191
Radiology. 2024 09;312(3): e242011

Biomarkers for Personalized Neoadjuvant Therapy in Triple-Negative Breast Cancer: Moving Forward.

Gaiane M Rauch.

DOI: https://doi.org/10.1148/radiol.242011
Int J Gynecol Cancer. 2024 Aug 28. pii: ijgc-2024-005700. [Epub ahead of print]

Molecular biology as a driver in therapeutic choices for ovarian cancer.

Martina Arcieri, Claudia Andreetta, Veronica Tius, Giulia Zapelloni, Francesca Titone, Stefano Restaino, Giuseppe Vizzielli.

  The majority of patients with ovarian cancer relapse within 3 years of first line chemotherapy. Therefore, choosing the most appropriate treatment in the recurrence setting has a fundamental role in defining a patient's prognosis. Treatment options include systemic and intra-peritoneal chemotherapy, secondary cytoreductive surgery, and stereotactic body radiotherapy. The best therapeutic choice depends on multiple factors and not only on treatment-free interval. For systemic therapy, prior lines therapy, residual toxicities, comorbidities, performance status, and patient preferences should be taken into account. Secondary cytoreductive surgery can be proposed in patients in which complete tumor resectability can be predicted and in those with oligometastatic disease. Stereotactic body radiotherapy represents a valid alternative to surgery for oligometastatic disease with high local control and minimal toxicity. Current evidence has demonstrated an emerging role of BRCA mutational status and molecular profiling in the impacting response to systemic and local treatments. Therefore, these could provide guidance in the treatment decision process and help identify patients who respond better to poly(ADP-ribose) polymerase (PARP)-inhibitors or immunotherapy or to a combined approach with surgery rather than to platinum-based chemotherapy. Current knowledge in this field could help widen therapeutic options, especially for platinum-resistant patients. In this review, we offer an overview of the state of the art regarding the role of chemotherapy, radiotherapy, and surgery in this setting and their implications in clinical practice and in the treatment decision process, so as to provide the best tailored therapy in patients with recurrent ovarian cancer.

Keywords:  Cytoreduction surgical procedures; Medical Oncology; Ovarian Cancer; Radiation Oncology

DOI:  https://doi.org/10.1136/ijgc-2024-005700
Cancer Cell. 2024 Aug 23. pii: S1535-6108(24)00309-X. [Epub ahead of print]

Precision oncology across the ages: Impact on children, adolescents, and young adults.

Vivek Subbiah, Razelle Kurzrock.

Precision oncology endeavors to tailor therapies based on individual patient and tumor characteristics. This rapidly evolving field has transformed cancer treatment across all age groups. In this commentary, we review the application of precision oncology across different age groups, specifically in children, adolescents, and young adults, and emphasize that precision medicine is age and tissue agnostic.

DOI: https://doi.org/10.1016/j.ccell.2024.08.010
Cancer Treat Res. 2024 ;192 277-303

Immunotherapy in Gastrointestinal Cancers.

Hazel Lote, Ian Chau.

  Immunotherapy has revolutionised cancer treatment over the past decade. Long-term durable responses can be achieved in some cancer patient populations that were previously facing terminal disease. In this chapter, we summarise current phase 3 clinical trial evidence for the use of immunotherapy in gastrointestinal cancers (oesophageal squamous cell carcinoma, oesophago-gastric adenocarcinoma, pancreatic cancer, biliary cancer, hepatocellular carcinoma, colorectal cancer, and squamous cell cancer of the anus). We discuss meaningful biomarkers used in clinical trials to select patients most likely to benefit from immunotherapy, such as mismatch-repair deficiency (MMRd)/microsatellite instability (MSI) and programmed-death-ligand-1 (PD-L1) immunohistochemistry (IHC) expression. Clinical questions are arising regarding the role of immunotherapy in the adjuvant/perioperative setting, optimal timing of surgery in patients who respond to immunotherapy, and toxicities specific to patients with gastrointestinal malignancies. We outline the current landscape and future horizon of immunotherapy in gastrointestinal cancers, such as strategies to increase effectiveness of checkpoint blockade through combinations with other checkpoint inhibitors, cytotoxic chemotherapy, targeted agents, radiotherapy, CAR-T therapy, and cancer vaccines.

Keywords:  Anal cancer; Biliary cancer; Checkpoint inhibition; Colorectal cancer; Gastrointestinal malignancies; Hepatocellular carcinoma; Immunotherapy; Oesophago-gastric cancer; PD-1 and PD-L1 inhibition; Pancreatic cancer

DOI:  https://doi.org/10.1007/978-3-031-61238-1_14
Cancer Med. 2024 Aug;13(16): e70083

Cost-effectiveness analysis of osimertinib plus chemotherapy for patients with EGFR-mutated advanced non-small cell lung cancer.

Wentao Tian, Lishui Niu, Rongrong Zhou, Ziqi Wang, Jiaoyang Ning, Ruoyu Lu, Yin Shi, Zhaohua Tan.

   INTRODUCTION: First-line osimertinib plus chemotherapy significantly prolonged progression-free survival of patients with EGFR-mutated advanced non-small cell lung cancer (NSCLC) compared to osimertinib, according to the FLAURA2 trial.
METHODS: We established a Markov model to compare the cost-effectiveness of osimertinib plus chemotherapy with that of osimertinib alone. Clinical data were obtained from the FLAURA and FLAURA2 trials, and additional data were extracted from online resources and publications. Sensitivity analyses were conducted to evaluate the robustness of the findings. We used A willingness-to-pay threshold of $150,000 per quality-adjusted life-years (QALYs) gained. The main outcomes were QALYs, overall costs, incremental cost-effectiveness ratio (ICER), incremental net monetary benefit, and incremental net health benefit. Subgroup analyses were conducted according to patients' mutation type and central nervous system (CNS) metastatic status.
RESULTS: In a 20-year time horizon, the ICER of osimertinib plus chemotherapy versus osimertinib alone was $223,727.1 per QALY gained. The sensitivity analyses identified the cost of osimertinib and the hazard ratio for overall survival as the top 2 influential factors and a 1.9% probability of osimertinib plus chemotherapy to be cost-effective. The subgroup analyses revealed ICERs of $132,614.1, $224,449.8, $201,464.1, and $130,159.7 per QALY gained for L858R mutations, exon 19 deletions, CNS metastases, and no CNS metastases subgroups, respectively.
CONCLUSIONS: From the perspective of the United States health care system, osimertinib plus chemotherapy is not cost-effective compared to osimertinib alone for treatment-naïve patients with EGFR-mutated advanced NSCLC, but more favorable cost-effectiveness occurs in patients with L858R mutations and patients without baseline CNS metastases.

Keywords:  EGFR; chemotherapy; cost‐effectiveness; non‐small cell lung cancer; osimertinib

DOI:  https://doi.org/10.1002/cam4.70083
NPJ Precis Oncol. 2024 Sep 05. 8(1): 188

A multimodal neural network with gradient blending improves predictions of survival and metastasis in sarcoma.

Anthony Bozzo, Alex Hollingsworth, Subrata Chatterjee, Aditya Apte, Jiawen Deng, Simon Sun, William Tap, Ahmed Aoude, Sahir Bhatnagar, John H Healey.

The objective of this study is to develop a multimodal neural network (MMNN) model that analyzes clinical variables and MRI images of a soft tissue sarcoma (STS) patient, to predict overall survival and risk of distant metastases. We compare the performance of this MMNN to models based on clinical variables alone, radiomics models, and an unimodal neural network. We include patients aged 18 or older with biopsy-proven STS who underwent primary resection between January 1st, 2005, and December 31st, 2020 with complete outcome data and a pre-treatment MRI with both a T1 post-contrast sequence and a T2 fat-sat sequence available. A total of 9380 MRI slices containing sarcomas from 287 patients are available. Our MMNN accepts the entire 3D sarcoma volume from T1 and T2 MRIs and clinical variables. Gradient blending allows the clinical and image sub-networks to optimally converge without overfitting. Heat maps were generated to visualize the salient image features. Our MMNN outperformed all other models in predicting overall survival and the risk of distant metastases. The C-Index of our MMNN for overall survival is 0.77 and the C-Index for risk of distant metastases is 0.70. The provided heat maps demonstrate areas of sarcomas deemed most salient for predictions. Our multimodal neural network with gradient blending improves predictions of overall survival and risk of distant metastases in patients with soft tissue sarcoma. Future work enabling accurate subtype-specific predictions will likely utilize similar end-to-end multimodal neural network architecture and require prospective curation of high-quality data, the inclusion of genomic data, and the involvement of multiple centers through federated learning.

DOI: https://doi.org/10.1038/s41698-024-00695-7
JCO Precis Oncol. 2024 Sep;8 e2400221

Genomic Landscape of Pancreatic Neuroendocrine Tumors and Implications for Clinical Practice.

Ana De Jesus-Acosta, Chirayu Mohindroo.

Pancreatic neuroendocrine tumors (pNETs) are the second most prevalent neoplasms of the pancreas with variable prognosis and clinical course. Our knowledge of the genetic alterations in patients with pNETs has expanded in the past decade with the availability of whole-genome sequencing and germline testing. This review will focus on potential clinical applications of the genetic testing in patients with pNETs. For somatic testing, we discuss the commonly prevalent somatic mutations and their impact on prognosis and treatment of patients with pNET. We also highlight the relevant genomic biomarkers that predict response to specific treatments. Previously, germline testing was only recommended for high-risk patients with syndromic features (MEN1, VHL, TSC, and NF1), we review the evolving paradigm of germline testing in pNETs as recent studies have now shown that sporadic-appearing pNETs can also harbor germline variants.

DOI: https://doi.org/10.1200/PO.24.00221