Lung CancerCINSBDRILCPNCT04203095
Chromosomal Instability as a Surrogate Biomarker of Drug Resistance in Immunotherapy for Lung Cancer Patients
An observational study of Lung Cancer, run by Shanghai Pulmonary Hospital, Shanghai, China at 1 site in China.
Trial 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. Read more about this study
- Who is it for?
- Ages 20 to 70 years
- Conditions the study is for
- Lung Cancer
- What is being tested?
- the level of plasma cfDNA CINs
- How many people
- 40 participants
- Where
- 1 siteChina
- Study dates
- 10 Nov 2019to 11 Nov 2021
- Phase
- Observational
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 20 to 70 years
- All sexes
- No healthy volunteers
- Adult, Older adult
Study population: Patients diagnosed with lung cancer in Shanghai Pulmonary Hospital (SPH) from Aug 2019 till the end of this study.
Who may be able to join
- 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.
Who cannot join
- 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.
Trial locations and contacts
1 site in 1 country.
China1 site, 1 recruiting
- Recruiting
Di Zheng
Shanghai, Shanghai Municipality
Di Du, PhD, 8615800706091 ext. 8615800706091, changzheng_pg@163.com
About this study
Official title: 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.
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.
- Conditions
- Lung Cancer
- Being tested
- the level of plasma cfDNA CINs
- Keywords
- Chromosomal aneuploidy detection, lung cancer, PD-1/PD-L1, Drug resistance in Immunotherapy
- Medical subject headings
- Lung Neoplasms
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
the level of plasma cfDNA CINsDiagnostic test
The extracted cfDNA from PB will be analyzed by UCAD to determine the level of CINs.
| Study group | Role | What they receive |
|---|---|---|
| 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. Receives: Diagnostic Test: the level of plasma cfDNA CINs |
What is being measured
The primary outcome is the main question the study is designed to answer.
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.
Measured: 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.
Measured: through study completion, an average of 3 months
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted18 Dec 2019
- Study start10 Nov 2019
- Primary completion11 Nov 2020 (estimated)
- Study completion11 Nov 2021 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (17)Papers the sponsor has linked to this study.
- Other trials for Lung CancerStudies of the same condition, open and under way.
- More trials run by Shanghai Pulmonary Hospital, Shanghai, ChinaThe sponsor's other registered studies.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Case-control
- Time perspective
- Prospective
- Enrolment
- 40 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Shanghai Pulmonary Hospital, Shanghai, China
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Di Zheng, Shanghai Pulmonary Hospital, Shanghai, China
- Investigators
- Di Zheng, PhD, Study director, Shanghai Pulmonary Hospital, Shanghai, China
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT04203095
- Sponsor's protocol ID
- ph-pg001
- Acronym
- CINSBDRILCP
- Status last verified
- Dec 2019
- First submitted
- 16 Dec 2019
- Last updated
- 24 Dec 2019
- Results posted
- No
- Data monitoring committee
- Yes
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Undecided
Publications
Pardoll DM. The blockade of immune checkpoints in cancer immunotherapy. Nat Rev Cancer. 2012 Mar 22;12(4):252-64. doi: 10.1038/nrc3239.
PubMed 22437870Brahmer JR, Tykodi SS, Chow LQ, Hwu WJ, Topalian SL, Hwu P, Drake CG, Camacho LH, Kauh J, Odunsi K, Pitot HC, Hamid O, Bhatia S, Martins R, Eaton K, Chen S, Salay TM, Alaparthy S, Grosso JF, Korman AJ, Parker SM, Agrawal S, Goldberg SM, Pardoll DM, Gupta A, Wigginton JM. Safety and activity of anti-PD-L1 antibody in patients with advanced cancer. N Engl J Med. 2012 Jun 28;366(26):2455-65. doi: 10.1056/NEJMoa1200694. Epub 2012 Jun 2.
PubMed 22658128Topalian 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 22658127Wan MT, Ming ME. Nivolumab versus ipilimumab in the treatment of advanced melanoma: a critical appraisal: ORIGINAL ARTICLE: Wolchok JD, Chiarion-Sileni V, Gonzalez R et al. Overall survival with combined nivolumab and ipilimumab in advanced melanoma. N Engl J Med 2017; 377:1345-56. Br J Dermatol. 2018 Aug;179(2):296-300. doi: 10.1111/bjd.16785. Epub 2018 Jun 5.
PubMed 29766492Sharma P, Hu-Lieskovan S, Wargo JA, Ribas A. Primary, Adaptive, and Acquired Resistance to Cancer Immunotherapy. Cell. 2017 Feb 9;168(4):707-723. doi: 10.1016/j.cell.2017.01.017.
PubMed 28187290Gong J, Chehrazi-Raffle A, Reddi S, Salgia R. Development of PD-1 and PD-L1 inhibitors as a form of cancer immunotherapy: a comprehensive review of registration trials and future considerations. J Immunother Cancer. 2018 Jan 23;6(1):8. doi: 10.1186/s40425-018-0316-z.
PubMed 29357948Estin CD, Stevenson U, Kahn M, Hellstrom I, Hellstrom KE. Transfected mouse melanoma lines that express various levels of human melanoma-associated antigen p97. J Natl Cancer Inst. 1989 Mar 15;81(6):445-8. doi: 10.1093/jnci/81.6.445.
PubMed 2918553Restifo NP, Smyth MJ, Snyder A. Acquired resistance to immunotherapy and future challenges. Nat Rev Cancer. 2016 Feb;16(2):121-6. doi: 10.1038/nrc.2016.2.
PubMed 26822578O'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 27951441Haratani 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 28407039Sansregret 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 29297505Lee 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 21363922Kuznetsova AY, Seget K, Moeller GK, de Pagter MS, de Roos JA, Durrbaum M, Kuffer C, Muller S, Zaman GJ, Kloosterman WP, Storchova Z. Chromosomal instability, tolerance of mitotic errors and multidrug resistance are promoted by tetraploidization in human cells. Cell Cycle. 2015;14(17):2810-20. doi: 10.1080/15384101.2015.1068482.
PubMed 26151317Jamal-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 28445112Xue Y, Martelotto L, Baslan T, Vides A, Solomon M, Mai TT, Chaudhary N, Riely GJ, Li BT, Scott K, Cechhi F, Stierner U, Chadalavada K, de Stanchina E, Schwartz S, Hembrough T, Nanjangud G, Berger MF, Nilsson J, Lowe SW, Reis-Filho JS, Rosen N, Lito P. An approach to suppress the evolution of resistance in BRAFV600E-mutant cancer. Nat Med. 2017 Aug;23(8):929-937. doi: 10.1038/nm.4369. Epub 2017 Jul 17.
PubMed 28714990
Study at a glance
From the registry record, last updated by the sponsor on 24 Dec 2019. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- 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
- ClinicalTrials.gov ID
- NCT04203095
- Acronym / sponsor ID
- CINSBDRILCP / ph-pg001
- Conditions
- Lung Cancer
- Keywords
- Chromosomal aneuploidy detection, lung cancer, PD-1/PD-L1, Drug resistance in Immunotherapy
- Study type
- Observational
- Recruitment status
- Unknown status
- Enrolment
- 40 participants (estimated)
- Lead sponsor
- Shanghai Pulmonary Hospital, Shanghai, ChinaUniversity, hospital or other
- Study start
- 10 Nov 2019 (actual)
- Primary completion
- 11 Nov 2020 (estimated)
- Study completion
- 11 Nov 2021 (estimated)
- First posted
- 18 Dec 2019 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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.
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 design
- Observational model
- Case-control
- Time perspective
- Prospective
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| patient with PD1 antibody treatment | – | Diagnostic Test: the level of plasma cfDNA CINsInvestigators 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. |
Who may qualify
- Ages
- 20 to 70 years
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- Patients diagnosed with lung cancer in Shanghai Pulmonary Hospital (SPH) from Aug 2019 till the end of this study.
Key inclusion criteria (4 listed)
- 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.
Key exclusion criteria (4 listed)
- 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.
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| the level of plasma cfDNA CINsThe extracted cfDNA from PB will be analyzed by UCAD to determine the level of CINs. | Diagnostic test | patient with PD1 antibody treatment |
Primary outcome
the concordance bettwen CINs and treatment outcomes The concordance between CINs and treatment outcomes
Time frame: through study completion, an average of 3 months
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.
1 secondary outcome
the concordance bettwen CINs and clinical monitoring
Time frame: through study completion, an average of 3 months
Results and safety
Results are not available in the source record.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 24 Dec 2019.
- Background: PubMed 22437870Pardoll DM. The blockade of immune checkpoints in cancer immunotherapy. Nat Rev Cancer. 2012 Mar 22;12(4):252-64. doi: 10.1038/nrc3239.
- Background: PubMed 22658128Brahmer JR, Tykodi SS, Chow LQ, Hwu WJ, Topalian SL, Hwu P, Drake CG, Camacho LH, Kauh J, Odunsi K, Pitot HC, Hamid O, Bhatia S, Martins R, Eaton K, Chen S, Salay TM, Alaparthy S, Grosso JF, Korman AJ, Parker SM, Agrawal S, Goldberg SM, Pardoll DM, Gupta A, Wigginton JM. Safety and activity of anti-PD-L1 antibody in patients with advanced cancer. N Engl J Med. 2012 Jun 28;366(26):2455-65. doi: 10.1056/NEJMoa1200694. Epub 2012 Jun 2.
- Background: PubMed 22658127Topalian 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.
- Background: PubMed 29766492Wan MT, Ming ME. Nivolumab versus ipilimumab in the treatment of advanced melanoma: a critical appraisal: ORIGINAL ARTICLE: Wolchok JD, Chiarion-Sileni V, Gonzalez R et al. Overall survival with combined nivolumab and ipilimumab in advanced melanoma. N Engl J Med 2017; 377:1345-56. Br J Dermatol. 2018 Aug;179(2):296-300. doi: 10.1111/bjd.16785. Epub 2018 Jun 5.
- Background: PubMed 28187290Sharma P, Hu-Lieskovan S, Wargo JA, Ribas A. Primary, Adaptive, and Acquired Resistance to Cancer Immunotherapy. Cell. 2017 Feb 9;168(4):707-723. doi: 10.1016/j.cell.2017.01.017.
- Background: PubMed 29357948Gong J, Chehrazi-Raffle A, Reddi S, Salgia R. Development of PD-1 and PD-L1 inhibitors as a form of cancer immunotherapy: a comprehensive review of registration trials and future considerations. J Immunother Cancer. 2018 Jan 23;6(1):8. doi: 10.1186/s40425-018-0316-z.
- Background: PubMed 2918553Estin CD, Stevenson U, Kahn M, Hellstrom I, Hellstrom KE. Transfected mouse melanoma lines that express various levels of human melanoma-associated antigen p97. J Natl Cancer Inst. 1989 Mar 15;81(6):445-8. doi: 10.1093/jnci/81.6.445.
- Background: PubMed 26822578Restifo NP, Smyth MJ, Snyder A. Acquired resistance to immunotherapy and future challenges. Nat Rev Cancer. 2016 Feb;16(2):121-6. doi: 10.1038/nrc.2016.2.
- Background: PubMed 27951441O'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.
- Background: PubMed 28407039Haratani 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.
- Background: PubMed 29297505Sansregret 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.
- Background: PubMed 21363922Lee 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.
- Individual participant dataSharing planned: Undecided
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Non Small Cell Lung Cancer
Active, not recruiting
Streamlined Geriatric and Oncological Evaluation Based On IC Technology
Breast Cancer, Comorbidities and Coexisting Conditions
RecruitingPhase 3
A Study Evaluating Sotorasib Platinum Doublet Combination Versus Pembrolizumab Platinum Doublet Combination as a Front-Line Therapy in Participants With Stage IV or Advanced Stage IIIB/C Nonsquamous Non-Small Cell Lung Cancers (CodeBreaK 202)
Non-Small Cell Lung Cancer (NSCLC)
Active, not recruitingPhase 2
Datopotamab Deruxtecan (Dato-DXd, DS-1062a) in Advanced and/or Unresectable Non-Small Cell Lung Cancer
Metastatic Lung Cancer, Advanced Non Small Cell Lung Cancer
Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Di Zheng, PhD study director
Shanghai Pulmonary Hospital, Shanghai, China
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Lung Cancer, run by Shanghai Pulmonary Hospital, Shanghai, China at 1 site in China.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 4 inclusion and 4 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: status not confirmed, as of the sponsor's last update on 24 Dec 2019. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in China. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
Results are not available in the source record.
How can a doctor refer a patient or contact the research team?
Contact Di Zheng, PhD (8613801683953 ext. 8613801683953, pulmonarysh_pg@126.com), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
the concordance bettwen CINs and treatment outcomes The concordance between CINs and treatment outcomes (time frame: through study completion, an average of 3 months). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT04203095, which also lists 17 linked publications.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 24 Dec 2019.