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Poster Display session

123TiP - Dynamic multi-omics integration modelto predict neoadjuvant therapy response in locally advanced rectal cancer

Date

07 Dec 2024

Session

Poster Display session

Presenters

Yandong Zhao

Citation

Annals of Oncology (2024) 35 (suppl_4): S1432-S1449. 10.1016/annonc/annonc1687

Authors

Y. Zhao1, Z. Liu2, F. He3, Q. Yao4, F. Pei5, J. Huang6

Author affiliations

  • 1 Department Of Pathology, The Sixth Affiliated Hospital, Sun Yat-sen University, 510655 - Guangzhou/CN
  • 2 Coloproctology, The Sixth Affiliated Hospital, Sun Yat-sen University, 510655 - Guangzhou/CN
  • 3 Radiation Oncology, The Sixth Affiliated Hospital, Sun Yat-sen University, 510655 - Guangzhou/CN
  • 4 The Sixth Affiliated Hospital, Sun Yat-Sen University, 510275 - Guangzhou/CN
  • 5 Department Of Colorectal Surgery, The Sixth Affiliated Hospital, Sun Yat-sen University, 510655 - Guangzhou/CN
  • 6 Surgery Of Colorectal Cancer, The Sixth Affiliated Hospital, Sun Yat-sen University, 510655 - Guangzhou/CN

Resources

This content is available to ESMO members and event participants.

Abstract 123TiP

Background

Neoadjuvant therapies have significantly enhanced the pathological complete response (pCR) rates and prognosis in colorectal cancer (CRC) patients. The increased pCR rates may correlate with reductions in carcinoembryonic antigen (CEA) levels, tumor size, circulating tumor DNA (ctDNA) levels, neutrophil-to-lymphocyte ratio (NLR), and enhanced signal on magnetic resonance imaging (MRI). Accurately predicting pCR after neoadjuvant therapy could inform the adoption of a watch and wait strategy for patients with locally advanced rectal cancer (LACR).

Trial design

This multicenter, prospective, observational phase II clinical study aims to develop and validate a dynamic multi-omics integration model for predicting pCR after neoadjuvant treatment in LACR (T3-4NxM0) patients. Specifically, it is the first prospective study to assess the predictive accuracy of this dynamic multi-omics model and determine its superiority over conventional prediction models based on single-modality imaging, pathology, or molecular biomarkers. Eligible patients will be prospectively enrolled, and pre-neoadjuvant treatment, during-treatment, and preoperative MRI scans, histopathology slides stained with hematoxylin and eosin (H&E), CEA, NLR, and ctDNA will be collected and annotated. Changes in these features along with preoperative multistage biopsy results will be incorporated into the prediction model to forecast individual achievement of pCR after neoadjuvant treatment. Predictive results will be validated with pathological tumor response evaluated from resected specimens. Key inclusion criteria include histologically confirmed rectal adenocarcinoma, clinical stage T3-4NxM0 and no history of previous chemoradiotherapy or colorectal surgery. Main exclusion criteria encompass complications requiring long-term use of immunosuppressive drugs, substance abuse, or social conditions interfering with study participation or assessment, and history of other malignant tumors within 5 years or evidence of distant metastases outside the pelvis preoperatively. The study aims to enroll 106 patients. The study is registered with ClinicalTrials.gov (NCT06364371) and is ongoing.

Clinical trial identification

NCT06364371.

Legal entity responsible for the study

The authors.

Funding

Has not received any funding.

Disclosure

All authors have declared no conflicts of interest.

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