| Literature DB >> 35734602 |
Qunli Xiong1, Zhu Zeng1, Yang Yang1, Ya Wang2, Yongfeng Xu1, Ying Zhou1, Jinlu Liu1, Zhiwei Zhang1, Meng Qiu1, Qing Zhu1.
Abstract
Background: Close to one third of colorectal cancer (CRC) patients are diagnosed with metastatic CRC (mCRC). Patients with wild-type RAS and BRAF usually receive anti-EGFR monoclonal antibody therapy containing cetuximab. Overall, 30-50% of mCRC patients are reported to harbor RAS mutations, and RAS mutation status should be assessed when considering EGFR inhibitor treatment according to mCRC biomarker guidelines. Of note, 0.67-2% of patients with CRC harbored a KRAS amplification. Here we reported a case of advanced rectal cancer with wild-type RAS and BRAF in a male patient who harbored a KRAS amplification during anti-EGFR treatment. Case Presentation: A 46-year-old man was diagnosed with rectal adenocarcinoma with liver metastases (cT3NxM1a, stage IVA). After receiving first-line irinotecan- fluorouracil chemotherapy (FOLFIRI) plus cetuximab, second-line capecitabine- oxaliplatin chemotherapy (XELOX) plus bevacizumab, and third-line regorafenib, he rechallenged FOLFIRI and cetuximab for seven cycles, achieving a prolonged survival of at least 5 months. The KRAS copy number of circulating tumor DNA (ctDNA) was assessed during treatment. Notably, apart from serum carbohydrate antigen 199 (CA199) and carcinoembryonic antigen (CEA), the change of plasm Kirsten Rat Sarcoma Viral Oncogene Homolog (KRAS) copy number appeared to strongly correlate with treatment response.Entities:
Keywords: Kirsten Rat Sarcoma Viral Oncogene Homolog (KRAS); anti-EGFR monoclonal antibody; biomarker; cetuximab; colorectal cancer; gene copy number
Year: 2022 PMID: 35734602 PMCID: PMC9207953 DOI: 10.3389/fonc.2022.872630
Source DB: PubMed Journal: Front Oncol ISSN: 2234-943X Impact factor: 5.738
Figure 1Representative magnetic resonance imaging (MRI) images of lesions. (A–D) Representative images of T1-weighted imaging (T1WI), T2-weighted imaging (T2WI), diffusion-weighted imaging (DWI), and apparent diffusion coefficient (ADC) in the liver. (E–I) Representative images of rectum lesions in the sagittal position and coronal position (T1WI, T2WI, DWI and ADC), respectively. Red arrows indicate typical liver or rectum lesions.
Figure 2Representative computed tomography (CT) images of liver lesions during treatment. (A) Before first-line treatment, the representative CT image of the liver. (B) Regular CT was used to assess treatment efficacy during first-line treatment containing FOLFIRI plus cetuximab. (C) Regular revision CT was used to assess treatment efficacy during second-line treatment containing XELOX plus bevacizumab. (D) CT image of liver lesions after two cycles of regorafenib. (E) CT images of liver lesions after two cycles and four cycles of rechallenging FOLFIRI plus cetuximab. Red arrows indicate typical liver lesions. CT computed tomography; FOLFIRI, chemotherapy regimen containing irinotecan and fluorouracil; XELOX, chemotherapy regimen containing capecitabine and oxaliplatin.
Figure 3Changes in KRAS copy number, CA199, and CEA level during anti-tumor treatment and follow-up of the patient. The KRAS copy number was measured in the patient’s circulating tumor DNA. The CA199 and CEA tumor markers were measured in the patient’s serum at periodic intervals throughout the clinical course and annotated with the date, therapeutic approach, and treatment efficacy. CA199, cancer antigen 199; CEA, carcinoembryonic antigen; SD, stable response; PR, partial response; FOLFIRI, chemotherapy regimen containing irinotecan and fluorouracil; XELOX, chemotherapy regimen containing capecitabine and oxaliplatin.
Literature of reported clinical trials of rechallenge with anti-epidermal growth factor receptor (EGFR) therapy with panitumumab or cetuximab-based therapy for patients with metastatic colorectal cancer.
| First author | Published year | Nation | Type of research | Number of patients | Median OS (months) | Median PFS (months) | ORR | DCR |
|---|---|---|---|---|---|---|---|---|
| Muhammad Wasif Saif ( | 2010 | USA | Retrospective | 15 | – | 4 | – | 40.0% |
| D. Santini ( | 2012 | Italy | Prospective (phase II) | 39 | – | 6.6 | 53.8% | 89.7% |
| Raymond C. Wadlow ( | 2012 | USA | Prospective (phase II) | 20 | 1.7 | 5.2 | 0.0% | 45.0% |
| Filippo Pietrantonio ( | 2013 | Italy | Retrospective | 30 | 9.6 | 4.2 | 30.0% | 67.0% |
| X. Liu ( | 2015 | USA | Retrospective | 89 | – | 4.9 | – | 58.0% |
| HIROAKI TANIOKA ( | 2018 | Japan | Retrospective | 14 | – | 4.4 | 21.4% | 71.4% |
| H. Osawa ( | 2018 | Japan | Prospective (phase II) | 33 | 8.7 | 2.9 | 15.6% | 56.2% |
| Chiara Cremolini ( | 2019 | Italy | Prospective (phase II) | 28 | 9.8 | 3.4 | 21.0% | 54.0% |
| Daniele Rossini ( | 2020 | Italy | Retrospective | 86 | 10.2 | 3.8 | 19.8% | – |
| Li Chia Chong ( | 2020 | Australia | Retrospective | 22 | 7.7 | 4.1 | 4.5% | 45.4% |
| Yu Sunakawa ( | 2020 | Japan | Prospective (phase II) | 58 | – | 2.4-3.1 | 2.9%-8.3% | – |
| Amanda Karani ( | 2020 | Brazil | Retrospective | 17 | 7.5 | 3.3 | 18.0% | – |
OS, overall survival; PFS, progression-free survival; CI, confidence interval; ORR, objective response rate; DCR, disease control rate; -, not mentioned in the literature.