A liquid biopsy signature predicts treatment response to fluoropyrimidine plus platinum therapy in patients with metastatic or unresectable gastric cancer: implications for precision oncology

With increasing knowledge on molecular tumour information, precision oncology has revolutionised the medical field over the past years. Liquid biopsy entails the analysis of circulating tumour components, such as circulating tumour DNA, tumour cells or tumour-derived extracellular vesicles, and has thus come as a handy tool for personalised medicine in many cancer entities. Clinical applications under investigation include early cancer detection, prediction of treatment response and molecular monitoring of the disease, for example, to comprehend resistance patterns and clonal tumour evolution. In fact, several tests for blood-based mutation profiling are already commercially available and have entered the clinical field.In the context of hepatocellular carcinoma, where access to tissue specimens remains mostly limited to patients with early stage tumours, liquid biopsy approaches might be particularly helpful. A variety of translational liquid biopsy studies have been carried out to address clinical needs, such as early hepatocellular carcinoma detection and prediction of treatment response. To this regard, methylation profiling of circulating tumour DNA has evolved as a promising surveillance tool for early hepatocellular carcinoma detection in populations at risk, which might soon transform the way surveillance programmes are implemented. This review summarises recent developments in the liquid biopsy oncological space and, in more detail, the potential implications in the clinical management of hepatocellular carcinoma. It further outlines technical peculiarities across liquid biopsy technologies, which might be helpful for interpretation by non-experts.

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Exploring miRNA Signature and Other Potential Biomarkers for Oligorecurrent Prostate Cancer Characterization: The Biological Challenge behind Clinical Practice. A Narrative Review

Cancers ◽

10.3390/cancers13133278 ◽

2021 ◽

Vol 13 (13) ◽

pp. 3278

Author(s):

Giulia Corrao ◽

Mattia Zaffaroni ◽

Luca Bergamaschi ◽

Matteo Augugliaro ◽

Stefania Volpe ◽

...

Keyword(s):

Prostate Cancer ◽

Treatment Response ◽

Liquid Biopsy ◽

Clinical Decision Making ◽

Predictive Biomarkers ◽

Narrative Review ◽

Histopathological Analysis ◽

Precision Oncology ◽

Clinical Implementation ◽

Metastatic Lesions

In recent years, a growing interest has been directed towards oligometastatic prostate cancer (OMPC), as patients with three to five metastatic lesions have shown a significantly better survival as compared with those harboring a higher number of lesions. The efficacy of local ablative treatments directed on metastatic lesions (metastases-directed treatments) was extensively investigated, with the aim of preventing further disease progression and delaying the start of systemic androgen deprivation therapies. Definitive diagnosis of prostate cancer is traditionally based on histopathological analysis. Nevertheless, a bioptic sample—static in nature—inevitably fails to reflect the dynamics of the tumor and its biological response due to the dynamic selective pressure of cancer therapies, which can profoundly influence spatio-temporal heterogeneity. Furthermore, even with new imaging technologies allowing an increasingly early detection, the diagnosis of oligometastasis is currently based exclusively on radiological investigations. Given these premises, the development of minimally-invasive liquid biopsies was recently promoted and implemented as predictive biomarkers both for clinical decision-making at pre-treatment (baseline assessment) and for monitoring treatment response during the clinical course of the disease. Through liquid biopsy, different biomarkers, commonly extracted from blood, urine or saliva, can be characterized and implemented in clinical routine to select targeted therapies and assess treatment response. Moreover, this approach has the potential to act as a tissue substitute and to accelerate the identification of novel and consistent predictive analytes cost-efficiently. However, the utility of tumor profiling is currently limited in OMPC due to the lack of clinically validated predictive biomarkers. In this scenario, different ongoing trials, such as the RADIOSA trial, might provide additional insights into the biology of the oligometastatic state and on the identification of novel biomarkers for the outlining of true oligometastatic patients, paving the way towards a wider ideal approach of personalized medicine. The aim of the present narrative review is to report the current state of the art on the solidity of liquid biopsy-related analytes such as CTCs, cfDNA, miRNA and epi-miRNA, and to provide a benchmark for their further clinical implementation. Arguably, this kind of molecular profiling could refine current developments in the era of precision oncology and lead to more refined therapeutic strategies in this subset of oligometastatic patients.

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DEEPGENTM—A Novel Variant Calling Assay for Low Frequency Variants

Genes ◽

10.3390/genes12040507 ◽

2021 ◽

Vol 12 (4) ◽

pp. 507

Author(s):

Bernd Timo Hermann ◽

Sebastian Pfeil ◽

Nicole Groenke ◽

Samuel Schaible ◽

Robert Kunze ◽

...

Keyword(s):

Cancer Detection ◽

Genetic Variants ◽

Liquid Biopsy ◽

Hot Spot ◽

Treatment Success ◽

Low Frequency ◽

Variant Calling ◽

Subsequent Treatment ◽

Precision Oncology ◽

Orthogonal Comparison

Detection of genetic variants in clinically relevant genomic hot-spot regions has become a promising application of next-generation sequencing technology in precision oncology. Effective personalized diagnostics requires the detection of variants with often very low frequencies. This can be achieved by targeted, short-read sequencing that provides high sequencing depths. However, rare genetic variants can contain crucial information for early cancer detection and subsequent treatment success, an inevitable level of background noise usually limits the accuracy of low frequency variant calling assays. To address this challenge, we developed DEEPGENTM, a variant calling assay intended for the detection of low frequency variants within liquid biopsy samples. We processed reference samples with validated mutations of known frequencies (0%–0.5%) to determine DEEPGENTM’s performance and minimal input requirements. Our findings confirm DEEPGENTM’s effectiveness in discriminating between signal and noise down to 0.09% variant allele frequency and an LOD(90) at 0.18%. A superior sensitivity was also confirmed by orthogonal comparison to a commercially available liquid biopsy-based assay for cancer detection.

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1506 Efficacy of palliative radiotherapy and chemoradiotherapy for localized bleeding and obstruction caused by unresectable gastric cancer

European Journal of Cancer ◽

10.1016/s0959-8049(16)30596-2 ◽

2015 ◽

Vol 51 ◽

pp. S206

Author(s):

S. Hiramoto ◽

A. Kikuchi ◽

A. Yoshioka ◽

I. Maeda

Keyword(s):

Gastric Cancer ◽

Palliative Radiotherapy ◽

Unresectable Gastric Cancer

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Treatment for unresectable gastric cancer

Journal of Korean Medical Association ◽

10.5124/jkma.2015.58.3.209 ◽

2015 ◽

Vol 58 (3) ◽

pp. 209 ◽

Cited By ~ 1

Author(s):

Tae-Yong Kim ◽

Do-Youn Oh ◽

Yung-Jue Bang

Keyword(s):

Gastric Cancer ◽

Unresectable Gastric Cancer

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PrediCTC, liquid biopsy in precision oncology: a technology transfer experience in the Spanish health system

Clinical & Translational Oncology ◽

10.1007/s12094-017-1760-9 ◽

2017 ◽

Vol 20 (5) ◽

pp. 630-638 ◽

Cited By ~ 1

Author(s):

L. Alonso-Alconada ◽

J. Barbazan ◽

S. Candamio ◽

J. L. Falco ◽

C. Anton ◽

...

Keyword(s):

Technology Transfer ◽

Health System ◽

Liquid Biopsy ◽

Precision Oncology ◽

Spanish Health

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Gastrojejunal Bypass in Advanced Unresectable Gastric Cancer

Nihon Gekakei Rengo Gakkaishi (Journal of Japanese College of Surgeons) ◽

10.4030/jjcs.36.908 ◽

2011 ◽

Vol 36 (6) ◽

pp. 908-912

Author(s):

Kaname Ishii ◽

Kazuhiro Mori

Keyword(s):

Gastric Cancer ◽

Unresectable Gastric Cancer

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Development and Validation of CT-based Radiomics Scores for Prediction of Response to Neoadjuvant Chemotherapy and Survival in Gastric Cancer

10.21203/rs.2.17517/v1 ◽

2019 ◽

Author(s):

Kai-Yu Sun ◽

Hang-Tong Hu ◽

Shu-Ling Chen ◽

Jin-Ning Ye ◽

Guang-Hua Li ◽

...

Keyword(s):

Gastric Cancer ◽

Neoadjuvant Chemotherapy ◽

Treatment Response ◽

Validation Cohort ◽

Clinical Score ◽

Feature Reduction ◽

Portal Venous Phase ◽

Clinical Variables ◽

Predicting Performance ◽

Significant Difference

Abstract Background: Neoadjuvant chemotherapy is a promising treatment option for potential resectable gastric cancer, but patients’ responses varied. We aimed to develop and validate a radiomics score (rad_score) to predict the treatment response of neoadjuvant chemotherapy, and to investigate its efficacy in survival stratification. Methods: A total of 106 patients with neoadjuvant chemotherapy before gastrectomy were included (training cohort: n=74; validation cohort: n=32). Radiomics features were extracted from the pre-treatment portal venous-phase CT. After feature reduction, a rad_score was established by Randomized Tree algorithm. A rad_clinical_score was constructed by integrating the rad_score with clinical variables, so was a clinical score by clinical variables only. The three scores were validated regarding their discrimination and clinical usefulness. According to the score thresholds (updated with post-operative clinical variables), patients were stratified into two groups and their survivals were compared.Results: In the validation cohort, the rad_score demonstrated a good predicting performance in treatment response of neoadjuvant chemotherapy (AUC [95% CI] =0.82 [0.67, 0.98]), which was better than the clinical score (based on pre-operative clinical variables) without significant difference (0.62 [0.42, 0.83], P=0.09). The rad_clinical_score could not further improve the performance of rad_score (0.70 [0.51, 0.88], P=0.16). Based on the thresholds of these scores, the high-score groups all achieved better survivals than the low-score groups in the whole cohort (all P<0.001). Conclusion: The rad_score was effective in predicting treatment response of neoadjuvant chemotherapy and stratifying patients’ survival for gastric cancer, which assisted in individualized treatment planning.

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