Chromosomal Instability as a Surrogate Biomarker of Drug Resistance in Immunotherapy for Lung Cancer Patients (CINSBDRILCP)

Dynamic Monitor of Serum Chromosomal Instability Detected by UCAD as a Surrogate Biomarker of Treatment Efficacy in PD1 Inhibitor Based Immunotherapy for Lung Cancer Patients

PD1, as an immune checkpoint inhibitor, has provided a new therapeutic approach for patients with cancer, including patients. Although immunotherapy has proven effective, most patients do not benefit from it because of a large proportion which developing primary and acquired resistance. However, there is still a lack of accurate and effective molecular biomarkers to accurately evaluate the drug resistance of patients treated with immune checkpoint inhibitors (ICI), so as to maximize the therapeutic effect in patients. Chromosomal instability (CIN) is one of the most prominent and common characteristics of solid tumors, accelerating the development of anti-cancer drug resistance, often leading to treatment failure and disease recurrence, which limits the effectiveness of most current treatments. Hence the aim of this study is to evaluate dynamic CIN continuously monitored in the blood of patients with lung cancer treated with ICIs with Ultrasensitive Chromosomal Aneuploidy Detection (UCAD) to establish a new molecular immune resistance evaluation index. Further, the correlation between the evolution of tumor cloning and ICI resistance in patients during treatment was analyzed based on the results of dynamic CIN detection. This not only evaluate the efficacy of the ICI treatment in real-time, but also enables better understanding and overcoming the resistance mechanism of immunotherapy in the future.

Study Overview

• Status: Unknown
• Conditions: Lung Cancer
• Intervention / Treatment: Diagnostic test: the level of plasma cfDNA CINs

Detailed Description

Immune checkpoint inhibitors (ICI) targeted to PD-1/PD-L1 axis has a higher response rate and lower incidence of side effects compared with anti-CTLA4, and has been proved to have survival advantages in many different malignant tumors, which has been approved as a second-line or first-line treatment for a growing number of malignancies, including lung cancer. As results of retrospective analysis led by Roberto Ferrara, although the efficacy of ICI treatment is obvious in non-small cell lung cancer (NSCLC), there are significant differences in efficacy and responsiveness in different patients. Therefore, establishing predictive biomarkers for immunotherapy is the key to maximizing the therapeutic effect and studying drug resistance. According to clinical trial data after immunotherapy, there are three main groups: (1) those who respond initially and continue to respond (responders); (2) those who have never responded (primary resistance); (3) Those who initially respond but eventually develop into disease progression (secondary resistance).Currently, PD-L1 expression is one of the most common biomarkers for immunotherapy, PD-L1 expression itself does not accurately predict immunotherapy response, due to that the many patients with higher PD-L1 have no response to clinical treatment, and many patients with lower PD-L1 respond better. Although tumor mutation burden (TMB ) used as a biomarker for the treatment of NSCLC by Opdivo could better differentiate the people who benefit compared with PD-L1, however, TMB as a biomarker to determine the criteria for the application of ICI treatment resistance is also limited because of its specific mechanism involved in tumor immune regulation needs to be further clarified and high cost of TMB detection using NGS for whole exome sequencing analysis.

As one of the most prominent and common features of solid tumors, chromosomal instability (CIN) accelerates the development of anticancer drug resistance, often leading to treatment failure and disease recurrence, which limits the effectiveness of most current treatments. Previous studies have shown that CIN promotes the emergence of multidrug resistance by providing higher levels of genetic diversity, leading to multidrug resistance. In NSCLC, the researchers found that genomic doubling and sustained dynamic CIN were associated with intratumoral heterogeneity and led to parallel evolution of CDNAs, including CDK4, FOXA1, and BCL11A. It is worth noting that the study found consistency in the variation of mutation levels, indicating that CIN in lung cancer is more likely to select driving events than other mutation processes. CIN enables cells to enter several different evolutionary trajectories and adapt to the selective pressure generated by treatment, which is the basis of drug resistance. Based on the above, CIN may become a more accurate and effective biomarker for the study of drug resistance mechanism of ICI in lung cancer. NGS technology can obtain more comprehensive genomic information while detecting cost reduction, making CIN detection more accurate and practical than FISH used for evaluating CIN in patient commonly.As a new Detection method based on NGS technology, Ultrasensitive Chromosomal Aneuploidy Detection (UCAD) has been developed in our previous study. In which, low-coverage whole-genome sequencing technology based on NGS was adopted to detect CIN of ctDNA in patients' peripheral blood, and bioinformatics analysis was performed to determine the risk of malignancy (or recurrence) and the extent of tumor burden and CIN. It has important clinical value in auxiliary diagnosis, therapeutic effect monitoring, recurrence and metastasis monitoring and prognosis evaluation of tumor patients.

This study proposes that continuous dynamic CIN is related to intratumor heterogeneity, which drives parallel evolution of somatic copy-number alterations (SCNAs) and promotes the emergence of drug-resistant clones by providing a higher level of genetic diversity of tumor cells, thus leading to drug resistance in patients treated with ICI. Investigators aimed to continuously monitor dynamic CIN in the blood of patients with lung cancer after second-line treatment with UCAD to establish a new molecular immune resistance evaluation index. Further, the correlation between the evolution of tumor cloning and ICI resistance in patients during treatment was analyzed based on the detection results of dynamic CIN.

• Study Type: Observational
• Enrollment (Anticipated): 40

Contacts and Locations

• Study Contact: Name: Di Zheng, PhD; Phone Number: 8613801683953 8613801683953; Email: pulmonarysh_pg@126.com
• Study Contact Backup: Name: Ziliang Qian, PhD; Phone Number: 8615000902318; Email: ziliang.qian@prophetgenomics.com.cn

Study Locations

• China
  • Shanghai
    • Shanghai, Shanghai, China
      • Recruiting
      • Di Zheng
      • Contact: Di Du, PhD; Phone Number: 8615800706091 8615800706091; Email: changzheng_pg@163.com

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: 20 years to 70 years (Adult, Older Adult)
• Accepts Healthy Volunteers: No
• Genders Eligible for Study: All

• Sampling Method: Non-Probability Sample

Study Population

Patients diagnosed with lung cancer in Shanghai Pulmonary Hospital (SPH) from Aug 2019 till the end of this study.

Description

Inclusion Criteria:

• Stage IIIa-IVb Non-small-cell lung cancer patients without EGFR，ALK,ROS1,c-Met driven gene mutation. Male or female patients aged 20-70 years.
• Patients planed to receive PD1 antibody treatment with or without chemotherapy, including as the neo-adjuvant therapy.
• The subjects' age, sex, marital and reproductive history, collection time, pathology, cytology and imaging diagnosis were complete.
• Participants signed informed consent form.

Exclusion Criteria:

• Eligible to target therapy with driven gene mutation.
• Without measurable target lesion according to the RECIST criteria.
• Age under 20 years or more than 70.
• Individuals unwilling to sign the consent form or unwilling to provide PB for test or unwilling to provide the medical record.

Study Plan

How is the study designed?

Number of groups / cohorts

1

Cohorts and Interventions

Group / Cohort	Intervention / Treatment
patient with PD1 antibody treatment; Investigators will detect cfDNA CIN of lung cancer patients 1day (Day 0) before treatment with PD1 antibody, then Day 22 and Day 64 after treatment with PD1 antibody, as well as at the time of disease progression confirmed. The correlation of CIN and drug resistance to PD1 antibody was analyzed.	Diagnostic test: the level of plasma cfDNA CINs; The extracted cfDNA from PB will be analyzed by UCAD to determine the level of CINs.

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
the concordance bettwen CINs and treatment outcomes The concordance between CINs and treatment outcomes	According to the correlation analysis between the patient's clinical drug resistance and CIN detected using UCAD, the stratified cutoff value interval of the patient was found, which was divided into four treatment outcomes based on CIN assessment : significant efficacy, primary drug resistance, acquired drug resistance and possible super progress.	through study completion, an average of 3 months

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
the concordance bettwen CINs and clinical monitoring	Analyze the correlation between the dynamic change of CIN using UCAD and the efficacy evaluation by the RECIST criteria , and compare the time difference and accuracy between UCAD and imaging test and serology.	through study completion, an average of 3 months

Collaborators and Investigators

• Sponsor: Shanghai Pulmonary Hospital, Shanghai, China
• Investigators: Study Director: Di Zheng, PhD, Shanghai Pulmonary Hospital, Shanghai, China

Publications and helpful links

General Publications

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Study record dates

Study Major Dates

• Study Start (Actual): November 10, 2019
• Primary Completion (Anticipated): November 11, 2020
• Study Completion (Anticipated): November 11, 2021

Study Registration Dates

• First Submitted: December 16, 2019
• First Submitted That Met QC Criteria: December 16, 2019
• First Posted (Actual): December 18, 2019

Study Record Updates

• Last Update Posted (Actual): December 24, 2019
• Last Update Submitted That Met QC Criteria: December 21, 2019
• Last Verified: December 1, 2019

More Information

Terms related to this study

• Keywords: lung cancer; PD-1/PD-L1; Chromosomal aneuploidy detection; Drug resistance in Immunotherapy
• Additional Relevant MeSH Terms: Pathologic Processes; Respiratory Tract Diseases; Neoplasms; Lung Diseases; Neoplasms by Site; Respiratory Tract Neoplasms; Thoracic Neoplasms; Chromosome Aberrations; Genomic Instability; Lung Neoplasms; Chromosomal Instability
• Other Study ID Numbers: ph-pg001

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: UNDECIDED

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No