92-Gene molecular profiling in identification of cancer origin: a retrospective study in Chinese population and performance within different subgroups

Cancer of unknown primary and the «seed and soil» hypothesis

The worldwide incidence rate of cancer of unknown primary (CUP) reaches 5% (Kang et al, 2021; Lee, Sanoff, 2020; Yang et al, 2022). CUP has an alarmingly high mortality rate, with 84% of patients succumbing within the first year following diagnosis (Registration and Service, 2018). Under normal circumstances, tumor cell metastasis follows the «seed and soil» hypothesis, displaying a tissue-specific pattern of cancer cell homing behavior based on the microenvironment composition of secondary organs. In this study, we questioned whether seed and soil concept applies to CUP, and whether the pattern of tumor and metastasis manifestations for cancer of known primary (CKP) can be used to inform diagnostic strategies for CUP. We compared data from metastatic and primary CUP foci to the metastasis patterns observed in CKP. Furthermore, we evaluated several techniques for identifying the tissue-of-origin (TOO) in CUP profiling, including DNA, RNA, and epigenetic TOO techniques.

SEOM-GETTHI clinical guideline for the practical management of molecular platforms (2021)

The improvement of molecular alterations in cancer as well as the development of technology has allowed us to bring closer to clinical practice the determination of molecular alterations in the diagnosis and treatment of cancer. The use of multidetermination platforms is spreading in most Spanish hospitals. The objective of these clinical practice guides is to review their usefulness, and establish usage guidelines that guide their incorporation into clinical practice.

CUP-AI-Dx: A tool for inferring cancer tissue of origin and molecular subtype using RNA gene-expression data and artificial intelligence

BACKGROUND

Cancer of unknown primary (CUP), representing approximately 3-5% of all malignancies, is defined as metastatic cancer where a primary site of origin cannot be found despite a standard diagnostic workup. Because knowledge of a patient's primary cancer remains fundamental to their treatment, CUP patients are significantly disadvantaged and most have a poor survival outcome. Developing robust and accessible diagnostic methods for resolving cancer tissue of origin, therefore, has significant value for CUP patients.

METHODS

We developed an RNA-based classifier called CUP-AI-Dx that utilizes a 1D Inception convolutional neural network (1D-Inception) model to infer a tumor's primary tissue of origin. CUP-AI-Dx was trained using the transcriptional profiles of 18,217 primary tumours representing 32 cancer types from The Cancer Genome Atlas project (TCGA) and International Cancer Genome Consortium (ICGC). Gene expression data was ordered by gene chromosomal coordinates as input to the 1D-CNN model, and the model utilizes multiple convolutional kernels with different configurations simultaneously to improve generality. The model was optimized through extensive hyperparameter tuning, including different max-pooling layers and dropout settings. For 11 tumour types, we also developed a random forest model that can classify the tumour's molecular subtype according to prior TCGA studies. The optimised CUP-AI-Dx tissue of origin classifier was tested on 394 metastatic samples from 11 tumour types from TCGA and 92 formalin-fixed paraffin-embedded (FFPE) samples representing 18 cancer types from two clinical laboratories. The CUP-AI-Dx molecular subtype was also independently tested on independent ovarian and breast cancer microarray datasets FINDINGS: CUP-AI-Dx identifies the primary site with an overall top-1-accuracy of 98.54% in cross-validation and 96.70% on a test dataset. When applied to two independent clinical-grade RNA-seq datasets generated from two different institutes from the US and Australia, our model predicted the primary site with a top-1-accuracy of 86.96% and 72.46% respectively.

INTERPRETATION

The CUP-AI-Dx predicts tumour primary site and molecular subtype with high accuracy and therefore can be used to assist the diagnostic work-up of cancers of unknown primary or uncertain origin using a common and accessible genomics platform.

FUNDING

NIH R35 GM133562, NCI P30 CA034196, Victorian Cancer Agency Australia.

Targeted sequencing identifies the mutational signature of double primary and metastatic malignancies: a case report

BACKGROUND

The accurate identification of the tissue of origin is critical for optimal management of cancer patients particularly those who develop multiple malignancies; however, conventional diagnostic methods at times may fail to provide conclusive diagnosis of the origin of the malignancy. Herein, we describe the use of targeted sequencing in distinguishing the primary and metastatic tumors in a patient with metachronous malignancies in the lung, colon and kidney.

CASE PRESENTATION

In December 2016, a 55-year-old Chinese male was diagnosed with stage IB lung adenosquamous carcinoma and treated with left lower lobectomy and 4 cycles of platinum-based chemotherapy. After being disease-free for 3.5 months, three colonic polyps were discovered and were diagnosed as invasive adenocarcinoma after polypectomy. Within 5.4 months from the polypectomy, squamous cell renal carcinoma was identified and was managed by radical nephrectomy. Immunohistochemistry results were inconclusive on the origin of the kidney tumor. Hence, the three archived surgical tissue samples were sequenced using a targeted panel with 520 cancer-related genes. Analysis revealed similar mutational signature between the lung and kidney tumors and a distinct mutational profile for the colon tumor, suggesting that the lung and colon malignancies were primary tumors, while the kidney tumor originated from the lung, revealing a diagnosis of metastatic double primary cancer - lung carcinoma with renal cell metastasis and second primary colon carcinoma.

CONCLUSION

Mutational profiling using targeted sequencing is valuable not only for the detection of actionable mutations, but also in the identification of the origin of tumors. This diagnostic approach should be considered in similar scenarios.

Integrating a 92-Gene Expression Analysis for the Management of Neuroendocrine Tumors of Unknown Primary

Background: Neuroendocrine tumors (NETs) are rare tumors that can originate from any part of the body. Often, imaging or exploratory surgery can assist in the identification of the tumor primary site, which is critical to the management of the disease. Neuroendocrine tumors (NETs) of unknown primary constitute approximately 10-15% of all NETs. Determining the original site of the tumor is critical to providing appropriate and effective treatment. Methods: We performed a retrospective review of neuroendocrine tumors at our institution between 2012 and 2016 using a 92-gene cancer ID analysis. Results: 56 patients with NETs of unknown primary were identified. Samples for 38 of the 56 underwent the 92-gene cancer ID analysis. The primary site of the tumor was identified with >95% certainty in 35 of the 38 patients. Conclusion: The 92-gene cancer ID analysis identified a primary site in 92% of our NETs study cohort that previously had been unknown. The results have direct implications on management of patients with regard to FDA-approved treatment options.

Capecitabine and Temozolomide in Neuroendocrine Tumor of Unknown Primary

Incidence of low grade well-differentiated neuroendocrine tumors (NET) is on the rise. The North American Neuroendocrine Tumor Society estimates that the United States has more than 150,000 gastroenteropancreatic NET patients. About 10% of metastatic NETs can be unknown primary, and due to their rarity, dedicated treatment algorithms and regimens are not defined. Combination of capecitabine and temozolomide (CAPTEM) is one of the systemic treatments used in gastroenteropancreatic NETs. We explored clinical activity of CAPTEM in NET of unknown primary. Methods. Retrospective review of NET of unknown primary managed at the University of Kentucky over the past five years (2012–2016). Result. 56 patients with NET of unknown primary were identified; 12 patients were treated with CAPTEM. Median progression-free survival on CAPTEM in grade II and grade III NET of unknown primary was 10.8 and 7 months, respectively. Six patients showed reduction in metastatic tumor volume at three-month CT scan. Three patients had stable disease and three patients showed disease progression at the first surveillance scan. Common side-effects were as follows: four patients developed grade II thrombocytopenia, three patients developed grade I lymphocytopenia, and two patients developed hand foot syndrome (grades I and III). Six patients developed grade I fatigue. Conclusion. CAPTEM should be considered for grades I and II NET of unknown primary, especially in the case of visceral crisis or bulky disease.

Molecular diagnostic testing in breast cancer

OBJECTIVES

An overview of molecular tests used in the treatment of breast cancer, organized by stage and clinical condition.

DATA SOURCES

Systematic review of scientific literature, guideline recommendations, and data published by test manufacturers.

CONCLUSION

Several molecular tests that analyze expression of cancer-related genes have been validated in clinical trials and are recommended by clinical practice guidelines to inform diagnosis and treatment decisions for personalized interventions.

IMPLICATIONS FOR NURSING PRACTICE

Molecular testing has become an important part of patient care for those with breast cancer. Oncology nurses must understand this methodology to prescribe tests, interpret the results, and provide guidance to patients.