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Status unknownNCT04203095CINSBDRILCPUpdated Dec 24, 2019

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

An observational study in Lung Cancer, sponsored by Shanghai Pulmonary Hospital, Shanghai, China. Status unknown at 1 site in China. Open to participants aged 20 Years to 70 Years. Per ClinicalTrials.gov, last updated 2019-12-24.

Sponsored by Shanghai Pulmonary Hospital, Shanghai, China · Observational

The sponsor has not verified this record recently (last verified Dec 2019), so the status shown — last known as Recruiting — may be out of date.
Study type
Observational
Model
Case-control
Time perspective
Prospective
Enrollment
40
Ages
20 Years to 70 Years
Sex
All
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Study summary

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.

Read the 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.

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Conditions studied

  • Lung Cancer

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Keywords

  • Chromosomal aneuploidy detection
  • lung cancer
  • PD-1/PD-L1
  • Drug resistance in Immunotherapy
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In context

Lung Neoplasms

7,243 studies on the registry are indexed under Lung Neoplasms; 1,558 are open to participants now.

This study's planned enrollment of 40 is below the median of 189 across 1,512 observational studies indexed under Lung Neoplasms.

Browse Lung Neoplasms studies →

Lead sponsor

Shanghai Pulmonary Hospital, Shanghai, China is the lead sponsor of 149 studies on the registry; 91 are open to participants now.

Counted across the registry records on this site, refreshed daily.

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Who can participate

Ages eligible
20 Years to 70 Years
Sexes eligible
All
Accepts healthy volunteers
No
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.

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

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.
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Study design

Observational model
Case-control
Time perspective
Prospective
Enrollment
40 participants (estimated)
Patient registry
No
Biospecimen retention
Samples with dna

Groups and cohorts

  • 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

Interventions

  • Diagnostic testthe level of plasma cfDNA CINs

    The extracted cfDNA from PB will be analyzed by UCAD to determine the level of CINs.

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What researchers measure

Primary outcomes

  1. 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.

    Time frame: through study completion, an average of 3 months

Secondary outcomes

  1. 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.

    Time frame: through study completion, an average of 3 months

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Study locations

1 of 1 sites recruiting
  • Di Zheng
    Shanghai, Shanghai, China
    Recruiting
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References and documents

Publications

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  • Topalian SL, Hodi FS, Brahmer JR, Gettinger SN, Smith DC, McDermott DF, Powderly JD, Carvajal RD, Sosman JA, Atkins MB, Leming PD, Spigel DR, Antonia SJ, Horn L, Drake CG, Pardoll DM, Chen L, Sharfman WH, Anders RA, Taube JM, McMiller TL, Xu H, Korman AJ, Jure-Kunkel M, Agrawal S, McDonald D, Kollia GD, Gupta A, Wigginton JM, Sznol M. Safety, activity, and immune correlates of anti-PD-1 antibody in cancer. N Engl J Med. 2012 Jun 28;366(26):2443-54. doi: 10.1056/NEJMoa1200690. Epub 2012 Jun 2. PubMed 22658127 ↗
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  • O'Donnell JS, Long GV, Scolyer RA, Teng MW, Smyth MJ. Resistance to PD1/PDL1 checkpoint inhibition. Cancer Treat Rev. 2017 Jan;52:71-81. doi: 10.1016/j.ctrv.2016.11.007. Epub 2016 Nov 27. PubMed 27951441 ↗
  • Haratani K, Hayashi H, Tanaka T, Kaneda H, Togashi Y, Sakai K, Hayashi K, Tomida S, Chiba Y, Yonesaka K, Nonagase Y, Takahama T, Tanizaki J, Tanaka K, Yoshida T, Tanimura K, Takeda M, Yoshioka H, Ishida T, Mitsudomi T, Nishio K, Nakagawa K. Tumor immune microenvironment and nivolumab efficacy in EGFR mutation-positive non-small-cell lung cancer based on T790M status after disease progression during EGFR-TKI treatment. Ann Oncol. 2017 Jul 1;28(7):1532-1539. doi: 10.1093/annonc/mdx183. PubMed 28407039 ↗
  • Sansregret L, Vanhaesebroeck B, Swanton C. Determinants and clinical implications of chromosomal instability in cancer. Nat Rev Clin Oncol. 2018 Mar;15(3):139-150. doi: 10.1038/nrclinonc.2017.198. Epub 2018 Jan 3. PubMed 29297505 ↗
  • Lee AJ, Endesfelder D, Rowan AJ, Walther A, Birkbak NJ, Futreal PA, Downward J, Szallasi Z, Tomlinson IP, Howell M, Kschischo M, Swanton C. Chromosomal instability confers intrinsic multidrug resistance. Cancer Res. 2011 Mar 1;71(5):1858-70. doi: 10.1158/0008-5472.CAN-10-3604. PubMed 21363922 ↗
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  • Jamal-Hanjani M, Wilson GA, McGranahan N, Birkbak NJ, Watkins TBK, Veeriah S, Shafi S, Johnson DH, Mitter R, Rosenthal R, Salm M, Horswell S, Escudero M, Matthews N, Rowan A, Chambers T, Moore DA, Turajlic S, Xu H, Lee SM, Forster MD, Ahmad T, Hiley CT, Abbosh C, Falzon M, Borg E, Marafioti T, Lawrence D, Hayward M, Kolvekar S, Panagiotopoulos N, Janes SM, Thakrar R, Ahmed A, Blackhall F, Summers Y, Shah R, Joseph L, Quinn AM, Crosbie PA, Naidu B, Middleton G, Langman G, Trotter S, Nicolson M, Remmen H, Kerr K, Chetty M, Gomersall L, Fennell DA, Nakas A, Rathinam S, Anand G, Khan S, Russell P, Ezhil V, Ismail B, Irvin-Sellers M, Prakash V, Lester JF, Kornaszewska M, Attanoos R, Adams H, Davies H, Dentro S, Taniere P, O'Sullivan B, Lowe HL, Hartley JA, Iles N, Bell H, Ngai Y, Shaw JA, Herrero J, Szallasi Z, Schwarz RF, Stewart A, Quezada SA, Le Quesne J, Van Loo P, Dive C, Hackshaw A, Swanton C; TRACERx Consortium. Tracking the Evolution of Non-Small-Cell Lung Cancer. N Engl J Med. 2017 Jun 1;376(22):2109-2121. doi: 10.1056/NEJMoa1616288. Epub 2017 Apr 26. PubMed 28445112 ↗
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  • Juric D, Castel P, Griffith M, Griffith OL, Won HH, Ellis H, Ebbesen SH, Ainscough BJ, Ramu A, Iyer G, Shah RH, Huynh T, Mino-Kenudson M, Sgroi D, Isakoff S, Thabet A, Elamine L, Solit DB, Lowe SW, Quadt C, Peters M, Derti A, Schegel R, Huang A, Mardis ER, Berger MF, Baselga J, Scaltriti M. Convergent loss of PTEN leads to clinical resistance to a PI(3)Kalpha inhibitor. Nature. 2015 Feb 12;518(7538):240-4. doi: 10.1038/nature13948. Epub 2014 Nov 17. PubMed 25409150 ↗
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Individual participant data

Plan to share: Undecided

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Updates

Tracking since Sep 25, 2026
No changes since tracking began. The registry record was last updated on Dec 24, 2019, before this site started recording changes on Sep 25, 2026. Its history is on ClinicalTrials.gov ↗
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Registry details

Key details

Study ID
NCT04203095
Lead sponsor
Shanghai Pulmonary Hospital, Shanghai, China
Responsible party
Di Zheng (Director of medical oncology, Shanghai Pulmonary Hospital, Shanghai, China) — Principal investigator
First posted
Dec 18, 2019
Start date
Nov 10, 2019
Primary completion
Nov 11, 2020 (estimated)
Completion
Nov 11, 2021 (estimated)
Last update
Dec 24, 2019

Study contacts

Di Zheng, PhD
Contact
pulmonarysh_pg@126.com
8613801683953 ext. 8613801683953
ziliang qian, PhD
Contact
ziliang.qian@prophetgenomics.com.cn
8615000902318
Di Zheng, PhD
study director · Shanghai Pulmonary Hospital, Shanghai, China

Oversight

Data monitoring committee
Yes
FDA-regulated drug
No
FDA-regulated device
No
View the source record on ClinicalTrials.gov ↗

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