High-Throughput Antigen Microarray Identifies Longitudinal Prognostic Autoantibody for Chemoimmunotherapy in Advanced Non-Small Cell Lung Cancer.

Chemoimmunotherapy has evolved as a standard treatment for advanced non-small cell lung cancer (aNSCLC). However, inevitable drug resistance has limited its efficacy, highlighting the urgent need for biomarkers of chemoimmunotherapy. A three-phase strategy to discover, verify, and validate longitudinal predictive autoantibodies (AAbs) for aNSCLC before and after chemoimmunotherapy was employed. A total of 528 plasma samples from 267 aNSCLC patients before and after anti-PD1 immunotherapy were collected, plus 30 independent formalin-fixed paraffin-embedded samples. Candidate AAbs were firstly selected using a HuProt high-density microarray containing 21,000 proteins in the discovery phase, followed by validation using an aNSCLC-focused microarray. Longitudinal predictive AAbs were chosen for ELISA based on responders versus non-responders comparison and progression-free survival (PFS) survival analysis. Prognostic markers were also validated using immunohistochemistry and publicly available immunotherapy datasets. We identified and validated a panel of two AAbs (MAX and DHX29) as pre-treatment biomarkers and another panel of two AAbs (MAX and TAPBP) as on-treatment predictive markers in aNSCLC patients undergoing chemoimmunotherapy. All three AAbs exhibited a positive correlation with early responses and PFS (p < 0.05). The kinetics of MAX AAb showed an increasing trend in responders (p < 0.05) and a tendency to initially increase and then decrease in non-responders (p < 0.05). Importantly, MAX protein and mRNA levels effectively discriminated PFS (p < 0.05) in aNSCLC patients treated with immunotherapy. Our results present a longitudinal analysis of changes in prognostic AAbs in aNSCLC patients undergoing chemoimmunotherapy.

Proteomics Identifies Circulating TIMP-1 as a Prognostic Biomarker for Diffuse Large B-Cell Lymphoma.

Diffuse large B-cell lymphoma (DLBCL) is a heterogeneous disease, although disease stratification using in-depth plasma proteomics has not been performed to date. By measuring more than 1000 proteins in the plasma of 147 DLBCL patients using data-independent acquisition mass spectrometry and antibody array, DLBCL patients were classified into four proteomic subtypes (PS-I-IV). Patients with the PS-IV subtype and worst prognosis had increased levels of proteins involved in inflammation, including a high expression of metalloproteinase inhibitor-1 (TIMP-1) that was associated with poor survival across two validation cohorts (n = 180). Notably, the combination of TIMP-1 with the international prognostic index (IPI) identified 64.00% to 88.24% of relapsed and 65.00% to 80.49% of deceased patients in the discovery and two validation cohorts, which represents a 24.00% to 41.67% and 20.00% to 31.70% improvement compared to the IPI score alone, respectively. Taken together, we demonstrate that DLBCL heterogeneity is reflected in the plasma proteome and that TIMP-1, together with the IPI, could improve the prognostic stratification of patients.

Identification of novel prognostic autoantibodies in diffuse large B-cell lymphoma treated with rituximab plus cyclophosphamide, doxorubicin, vincristine, and prednisone via a high-throughput antigen microarray.

BACKGROUND: R-CHOP (rituximab plus cyclophosphamide, doxorubicin, vincristine, and prednisone) is a standard first-line treatment for diffuse large B-cell lymphoma (DLBCL). However, 20%-40% of patients survive less than 5 years. Novel prognostic biomarkers remain in demand. METHODS: Baseline plasma autoantibodies (AAbs) were assessed in 336 DLBCLs. In the discovery phase (n = 20), a high-density antigen microarray (∼21,000 proteins) was used to expound AAb profiles. In the verification phase (n = 181), with a DLBCL-focused microarray, comparative results based on event-free survival at 24 months (EFS24) and lasso Cox regression models of progression-free survival (PFS) and overall survival (OS) were integrated to identify potential biomarkers. They were further validated by enzyme-linked immunosorbent assay in validation phase 1 (n = 135) and a dynamic cohort (n = 12). In validation phase 2, a two-AAb-based risk score was established. They were further validated in an immunohistochemistry cohort (n = 55) and four independent Gene Expression Omnibus datasets (n = 1598). RESULTS: Four AAbs (CREB1, N4BP1, UBAP2, and DEAF1) were identified that showed associations with EFS24 status (p < .05) and superior PFS and OS (p < .05). A novel risk score model based on CREB1 and N4BP1 AAbs was developed to predict PFS with areas under the curve of 0.72, 0.71, 0.76, and 0.82 at 1, 3, 5, and 7 years, respectively, in DLBCL treated with R-CHOP independent of the International Prognostic Index (IPI) and provided significant additional recurrence risk discrimination (p < .05) for the IPI. CREB1 and N4BP1 proteins and messenger RNAs were also associated with better PFS and OS (p < .05). CONCLUSIONS: This study identified a novel prognostic panel of CREB1, N4BP1, DEAF1, and UBAP2 AAbs that is independent of the IPI in DLBCL.

Longitudinal plasma proteomic analysis identifies biomarkers and combinational targets for anti-PD1-resistant cancer patients.

The response rate of anti-PD1 therapy is limited, and the influence of anti-PD1 therapy on cancer patients is unclear. To address these challenges, we conducted a longitudinal analysis of plasma proteomic changes with anti-PD1 therapy in non-small cell lung cancer (NSCLC), alveolar soft part sarcoma (ASPS), and lymphoma patients. We included 339 plasma samples before and after anti-PD1 therapy from 193 patients with NSCLC, ASPS, or lymphoma. The plasma proteins were detected using data-independent acquisition-mass spectrometry and customable antibody microarrays. Differential proteomic characteristics in responders (R) and non-responders (NR) before and after anti-PD1 therapy were elucidated. A total of 1019 proteins were detected using our in-depth proteomics platform and distributed across 10-12 orders of abundance. By comparing the differential plasma proteome expression between R and NR groups, 50, 206, and 268 proteins were identified in NSCLC, ASPS, and lymphoma patients, respectively. Th17, IL-17, and JAK-STAT signal pathways were identified upregulated in NR group, while cellular senescence and transcriptional misregulation pathways were activated in R group. Longitudinal proteomics analysis revealed the IL-17 signaling pathway was downregulated after treatment. Consistently, many proteins were identified as potential combinatorial therapeutic targets (e.g., IL-17A and CD22). Five noninvasive biomarkers (FLT4, SFTPB, GNPTG, F5, and IL-17A) were further validated in an independent lymphoma cohort (n = 39), and another three noninvasive biomarkers (KIT, CCL3, and TNFSF1) were validated in NSCLC cohort (n = 76). Our results provide molecular insights into the anti-PD1 therapy in cancer patients and identify new therapeutic strategies for anti-PD1-resistant patients.

Human Autoantigen Atlas: Searching for the Hallmarks of Autoantigens.

Understanding autoimmunity to endogenous proteins is crucial in diagnosing and treating autoimmune diseases. In this work, we developed a user-friendly AAgAtlas portal (http://biokb.ncpsb.org.cn/aagatlas_portal/index.php#), which can be used to search for 8045 non-redundant autoantigens (AAgs) and 47 post-translationally modified AAgs against 1073 human diseases that are prioritized by a credential score developed by multisource evidence. Using AAgAtlas, the immunogenic properties of human AAgs was systematically elucidated according to their genetic, biophysical, cytological, expression profile, and evolutionary characteristics. The results indicated that human AAgs are evolutionally conserved in protein sequence and enriched in three hydrophilic and polar amino acid residues (K, D, and E) that are located at the protein surface. AAgs are enriched in proteins that are involved in nucleic acid binding, transferase, and the cytoskeleton. Genome, transcriptome, and proteome analyses further indicated that AAb production is associated with gene variance and abnormal protein expression related to the pathological activities of different tumors. Collectively, our data outlines the hallmarks of human AAgs that facilitate the understanding of humoral autoimmunity and the identification of biomarkers of human diseases.

Identification of novel serological autoantibodies in Chinese prostate cancer patients using high-throughput protein arrays.

Autoantibody (AAb) has a prominent role in prostate cancer (PCa), with few studies profiling the AAb landscape in Chinese patients. Therefore, the AAb landscape in Chinese patients was characterized using protein arrays. First, in the discovery phase, Huprot arrays outlined autoimmune profiles against ~ 21,888 proteins from 57 samples. In the verification phase, the PCa-focused arrays detected 25 AAbs selected from the discovery phase within 178 samples. Then, PCa was detected using a backpropagation artificial neural network (BPANN) model. In the validation phase, an enzyme-linked immunosorbent assay (ELISA) was used to validate four AAb biomarkers from 196 samples. Huprot arrays profiled distinct PCa, benign prostate diseases (BPD), and health AAb landscapes. PCa-focused array depicted that IFIT5 and CPOX AAbs could distinguish PCa from health with an area under curve (AUC) of 0.71 and 0.70, respectively. PAH and FCER2 AAbs had AUCs of 0.86 and 0.88 in discriminating PCa from BPD. Particularly, PAH AAb detected patients in the prostate-specific antigen (PSA) gray zone with an AUC of 0.86. Meanwhile, the BPANN model of 4-AAb (IFIT5, PAH, FCER2, CPOX) panel attained AUC of 0.83 among the two cohorts for detecting patients with gray-zone PSA. In the validation cohort, the IFIT5 AAb was upregulated in PCa compared to health (p < 0.001). Compared with BPD, PAH and FCER2 AAbs were significantly elevated in PCa (p = 0.012 and 0.039). We have demonstrated the first extensive profiling of autoantibodies in Chinese PCa patients, identifying novel diagnostic AAb biomarkers, especially for identification of gray-zone-PSA patients.

High-throughput and multi-phases identification of autoantibodies in diagnosing early-stage breast cancer and subtypes.

Autoantibodies (AAbs) targeted tumor-associated antigens (TAAs) have the potential for early detection of breast cancer. Here, 574 early-stage breast cancer (ES-BC) patients containing 4 subtypes (Luminal A, Luminal B, HER2+, TN), 126 benign breast disease (BBD) patients, and 199 normal healthy controls (NHC) were separated into three-phases to discover, verify, and validate AAbs. In discovery phase using high-throughput protein microarray, 37 AAbs with sensitivity of 31.25%-86.25% and specificity over 73% in ES-BC, and 40 AAbs with different positive rates between subtypes were identified as candidates. In verification phase, 18 AAbs were significantly increased compared with the Control (BBD and NHC) in focused array. Ten out of 18 AAbs exhibited a significant difference between subtypes (P < .05). In ELISA validation phase, 5 novel AAbs (anti-KJ901215, -FAM49B, -HYI, -GARS, -CRLF3) exhibited significantly higher levels in ES-BC compared with BBD/NHC (P < .05). The sensitivities of individual AAb and a 5-AAbs panel were 20.41%-28.57% and 38.78%, whereas the specificities were over 90% and 85.94%. Simultaneously, 4 AAbs except anti-GARS differed significantly between TN and non-TN subtype (P < .05). We constructed 3 random forest classifier models based on AAbs to discriminant ES-BC from Control or BBD, and to discern TN subtype, which yielded an area under the curve of 0.870, 0.860, and 0.875, respectively. Biological interaction analysis revealed 4 TAAs, except for KJ901215, that were associated with well known proteins of BC. This study discovered and stepwise validated 5 novel AAbs with the potential to diagnose ES-BC and discern TN subtype, indicating easy-to-detect and minimally invasive diagnostic value of serum AAbs ahead of biopsy for future application.

Anti-PD1/PDL1 IgG subclass distribution in ten cancer types and anti-PD1 IgG4 as biomarker for the long time survival in NSCLC with anti-PD1 therapy.

BACKGROUND: Antibodies targeting programmed cell death-1(PD1) and its ligand (PDL1) have revolutionized cancer therapy. However, little is known about the preexisted anti-PD1/PDL1 autoantibodies (AAbs) distribution in multiple cancer types, nor is their potential biomarker role for anti-PD1 therapy. METHOD: Plasma anti-PD1/PDL1 AAb IgG and subclasses (IgG1-4) were detected by enzyme-linked immune sorbent assay (ELISA) in 190 cancer patients, covering 10 cancer types (lung, breast, esophageal, colorectal, liver, prostatic, cervical, ovarian, gastric cancers and lymphoma), the comprehensive correlation of AAbs with multiple clinical parameters was analyzed. We further tested these AAbs in 76 non-small cell lung cancer (NSCLC) samples receiving anti-PD1 therapy, the association of AAbs level with survival was analyzed and validated in an independent cohort (n = 32). RESULTS: Anti-PD1/PDL1 AAb IgG were globally detected in 10 types of cancer patients. IgG1 and IgG2 were the major subtypes for anti-PD1/PDL1 AAbs. Correlation analysis revealed a distinct landscape between various cancer types. The random forest model indicated that IgG4 subtype was mostly associated with cancer. In discovery cohort of 76 NSCLC patients, high anti-PD1 IgG4 was associated with a reduced overall survival (OS, p = 0.019), not progression-free survival (PFS, p = 0.088). The negative association of anti-PD1 IgG4 with OS was validated in 32 NSCLC patients (p = 0.032). CONCLUSION: This study reports for the first time the distribution of preexisted anti-PD1/PDL1 AAb IgG and subclasses across 10 cancer types. Moreover, the anti-PD1 AAb IgG4 subclass was identified to associate with OS, which may serve as a potential biomarker for anti-PD1 therapeutic survival benefit in NSCLC patients.

Cytokines screening identifies MIG (CXCL9) for postoperative recurrence prediction in operated non-small cell lung cancer patients.

BACKGROUND: Exploration of reliable biomarkers most likely to identify non-small cell lung cancer (NSCLC) patients at high risk for recurrence after surgery is needed. METHODS: Quantibody® Human Cytokine Antibody 6000 was used as screening tool to measure serum levels of 280 cytokines in ten healthy individuals and nine samples from three NSCLC patients before operation, after operation and postoperative recurrence. Selected cytokines were validated in two independent sets (89 patients before surgery, 69 patients after surgery and 40 patients with postoperative recurrence for each set) using ELISA method. The association of the selected cytokine with clinicopathologic features was also evaluated. RESULTS: Thirty-six cytokines were declined after surgery and again elevated when recurrence. We selected MIG to be further assessed in 2 validation sets, the mean value of serum MIG levels in 396 NSCLC patients was 253.42 ± 274.48 pg/mL and was significantly higher than the level in 60 healthy controls (47.65 ± 33.23 pg/mL, P < 0.0001). The serum MIG levels were 366.36 ± 324.04 pg/mL pre-operation, 134.04 ± 127.52 pg/mL post-operation and 208.05 ± 239.39 pg/mL in recurrence in NSCLC patients. The serum MIG levels were significant differences among NSCLC patients of pre-operation, post-operation and recurrence and controls (P < 0.0001). Moreover, Serum MIG levels were decreased markedly after operation and notably increased when disease relapsed (P < 0.0005). Serum MIG levels trend to be higher in patients with male gender, older age, smoking habit, poor tumor differentiation, and non-adenocarcinoma histology. CONCLUSIONS: These data indicated that MIG might be an indicator of postoperative recurrence and help to identify NSCLC patient who was easy to relapse after surgery.

Anti-p53 autoantibody in blood as a diagnostic biomarker for colorectal cancer: A meta-analysis.

Serum autoantibodies against tumour-associated antigens are promising biomarkers for diagnosis of cancer. This review summarizes the available evidence pertaining to the diagnostic potential of autoantibodies studied in the context of colorectal cancer (CRC). A systematic literature search was conducted in three databases (PubMed, Cochrane Library and Embase). Data pertaining to a total of 145 autoantibodies published in 80 articles were reviewed. Of these, anti-p53 antibody was the most commonly studied autoantibody; thus, we performed a meta-analysis on anti-p53 antibody in 24 articles. According to the cut-off values used to determine positivity for anti-p53 antibody, we divided the included studies into five groups. Owing to the presence of threshold effect in groups 4 and 5 and non-threshold effect in groups 1 and 2, pooled analysis focused on group 3 using a fixed-effects model (Mantel-Haenszel). Group 3, determining the cut-off value based on the value of p53 antibody titre index, was comprised of five articles including 733 patients with CRC and 172 controls (126 healthy individuals and 46 benign diseases). The pooled sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, diagnostic odds ratio and summary area under the receiver operating characteristic curves were 0.21, 0.99, 12.26, 0.80, 15.46 and 0.87, respectively. Serum anti-p53 autoantibody may potentially help distinguish CRC from healthy controls or benign diseases; however, it should be used in combination with other indicators due to the low sensitivity. Our study provides insights for further exploration of the optimal combination of different tumour-associated antigens or autoantibodies for diagnosis of CRC.

Tracking longitudinal genetic changes of circulating tumor DNA (ctDNA) in advanced Lung adenocarcinoma treated with chemotherapy.

INTRODUCTION: Pemetrexed combined with platinum complexes can be used as first-line treatment for advanced non-squamous non-small cell lung cancer (NSCLC), however, the efficacy and safety is varying from individuals. There is a need to better understand the genetic variations associated with platinum response. MATERIALS AND METHODS: We performed next-generation sequencing (NGS) based on BGI Oseq-ctDNA panel to analyze 98 longitudinal plasma samples from 32 lung adenocarcinoma patients during platinum-based chemotherapy, and a bioinformatic pipeline was developed to detect point mutations. RESULTS: We found that mutation burden was decreased after chemotherapy, which reflected chemotherapy sensitivity, especially the frequency of C>G and C>A substitutions. Moreover, neoplastic cells carrying a specific set of somatic mutations, such as EGFR(L858R), KRAS (p.G12C) were obviously correlated with platinum treatment. In addition, the MAPK pathway was found to have a pivotal role in NSCLC and platinum based response. Finally, we found that smokers benefit less from platinum-based chemotherapy. CONCLUSIONS: Collectively, this work described the dynamic changes of ctDNA mutation status during platinum-based treatment, which may contribute to advanced lung adenocarcinoma patients stratification and precision treatment.

The role of radiotherapy in extensive-stage small cell lung cancer after durvalumab-based immunochemotherapy: A retrospective study.

BACKGROUND: The purpose of this study was to evaluate the safety and efficacy of subsequent radiotherapy (RT) following first-line treatment with durvalumab plus chemotherapy in patients with extensive-stage small cell lung cancer (ES-SCLC). METHODS: A total of 122 patients with ES-SCLC from three hospitals during July 2019 to December 2021 were retrospectively analyzed. Inverse probability of treatment weighting (IPTW) analysis was performed to address potential confounding factors. The primary focus of our evaluation was to assess the impact of RT on progression-free survival (PFS) and overall survival (OS). RESULTS: After IPTW analysis, 49 patients received durvalumab plus platinum-etoposide(EP) chemotherapy followed by RT (Durva + EP + RT) and 72 patients received immunochemotherapy (Durva + EP). The median OS was 17.2 months vs. 12.3 months (hazard ratio [HR]: 0.38, 95% CI: 0.17-0.85, P = 0.020), and the median PFS was 8.9 months vs. 5.9 months (HR: 0.56, 95% CI: 0.32-0.97, P = 0.030) in Durva + EP + RT and Durva + EP groups, respectively. Thoracic radiation therapy (TRT) resulted in longer OS (17.2 months vs. 14.7 months) and PFS (9.1 months vs. 7.2 months) compared to RT directed to other metastatic sites. Among patients with oligo-metastasis, RT also showed significant benefits, with a median OS of 17.4 months vs. 13.7 months and median PFS of 9.8 months vs. 5.9 months compared to no RT. Continuous durvalumab treatment beyond progression (TBP) prolonged OS compared to patients without TBP, in both the Durva + EP + RT (NA vs. 15.8 months, HR: 0.48, 95% CI: 0.14-1.63, P = 0.238) and Durva + EP groups (12.3 months vs. 4.3 months, HR: 0.29, 95% CI: 0.10-0.81, P = 0.018). Grade 3 or 4 adverse events occurred in 13 (26.5%) and 13 (18.1%) patients, respectively, in the two groups; pneumonitis was mostly low-grade. CONCLUSION: Addition of RT after first-line immunochemotherapy significantly improved survival outcomes with manageable toxicity in ES-SCLC.

Radiation therapy in the era of immune treatment for hepatocellular carcinoma.

Immune checkpoint inhibitors (ICIs) have revolutionized cancer treatment in recent years and provide new opportunities to treat hepatocellular carcinoma (HCC). To date, several ICIs have been approved by the FDA for advanced HCC in first-line or second-line therapy. Downstaging conversion therapy for potentially resectable HCC to provide opportunities for surgical intervention is challenging. ICIs have become a hot spot in this field due to their high response rate. However, HCC has various etiologies and can evade the immune system through multiple mechanisms, which limit the efficacy of ICI monotherapy and demand novel combination strategies. Radiation therapy (RT) is also a candidate for conversion therapy in HCC and is currently gaining increasing attention as a good combination partner with ICIs due to its ability to modulate the tumor microenvironment. In this review, we illustrate the current indications for ICIs and RT in HCC, the rationale for their synergistic combination, and the current clinical trials in combination therapy. We also speculate on predictive biomarkers and novel future strategies to further enhance the efficacy of this combination. This review aims to provide references for future research on radiation and immunotherapy to arrive at a promising new era of HCC treatment.

An immunosuppressive subtype of senescent tumor cells predicted worse immunotherapy response in lung adenocarcinoma.

Senescent tumor cells (STCs) can induce immunosuppression, promoting tumor progression and therapy resistance. However, the specific characteristics of immunosuppressive STC have not been thoroughly investigated. This study aimed to characterize and elucidate the immunosuppressive phenotype of STC in lung adenocarcinoma by employing single-cell and bulk transcriptomics, as well as serum proteomics profiling. We identified senescence-related genes specific to tumors and identified Cluster10 of STC as the immunomodulatory subtype. Cluster10 exhibited a distinct secretome dominated by cytokines such as CXCL1, CXCL2, and CXCL8 and showed activation of transcription factors associated with cytokine secretion, including NFKB1, RELA, and STAT3. Notably, Cluster10 demonstrated the highest degree of intercellular communication among all cell types, with interactions as LGALS9-TIM3 and MIF-CD74. Furthermore, Cluster10 showed significant associations with poor prognosis and diminished response to immunotherapy. Analysis of serum proteomics data from our in-house cohort identified CXCL8 as a potential marker for predicting immunotherapeutic outcomes.

Gut Streptococcus is a microbial marker for the occurrence and liver metastasis of pancreatic cancer.

Background: Gut microbiome plays an indispensable role in the occurrence and progression in various diseases. The incidence of pancreatic cancer (PC) and liver metastasis (PCLM) are high, most of them are found in advanced stage. Therefore, it is particularly necessary to search for predictive biomarkers, which are helpful for early detection and treatment, and thus improve the survival rate and quality of life of PC patients. Methods: We retrospectively analyzed 44 pancreatic cancer patients (P group, n = 44) and 50 healthy people (N group, n = 50) from March 21, 2021 and August 2, 2022. Among all PC patients, we divided them into liver metastasis group (LM group, n = 27) and non-liver metastasis group (non-LM group, n = 17). DNA was extracted and 16S ribosomal RNA (16S rRNA) gene sequencing was performed. SPSS was used for statistical analyses and all bioinformatics analyses were based on QIIME2, p < 0.05 were considered statistically significant. Results: The microbial richness and diversity of group P and LM were higher than that of group N and non-LM. LEfSe analysis found that Streptococcus was a significantly different microorganism, which was further identified by random forest (RF) model, and its ability to predict PC and PCLM was verified by ROC curve. Conclusion: We demonstrated significant differences in intestinal microbiome composition between PC patients and healthy people, and found that Streptococcus is a potential biomarker for early prediction of PC and PCLM, which is critical for early diagnosis of diseases.

Case report: A rare case of neutropenia caused by pembrolizumab in squamous lung cancer and literature review.

Background: Immune checkpoint inhibitors, including anti-PD-1 therapies, have prolonged overall survival in patients with a variety of cancers, and immunotherapy is sometimes associated with immune-related adverse events (irAEs); however, hematological toxicity, especially neutropenia, is rare. Case presentation: A 78-year-old man with squamous lung cancer, with brain metastasis, was treated with pembrolizumab and albumin-bound paclitaxel as first-line treatment for one cycle and changed to pembrolizumab plus anlotinib at the second cycle. After two therapy cycles, grade 4 neutropenia developed, which mainly contributed to irAEs. The patient was started on granulocyte colony-stimulating factor (G-CSF) but did not improve; he was then treated with corticosteroids, and neutrophil counts gradually returned to normal levels. However, the patient eventually died because of neurological problems. Conclusion: Grade 4 neutropenia associated with ICI, although rare, is often severe and presents with infectious complications; it needs to be diagnosed early, and clinicians should ensure prompt and proper management to such patients.

Development and validation of a UPLC-MS/MS method to quantitate anti-PD1 monoclonal antibody (Toripalimab), and comparison with electrochemiluminescence immunoassay.

Toripalimab, a humanized IgG4 monoclonal antibody (mAb) against programmed death receptor-1, is being extensively studied to treat various malignancies. At present, there is no complete methodology reported for quantifying toripalimab, except for an electrochemiluminescence immunoassay (ECLIA) mentioned in several clinical studies. Therefore, a sensitive and robust ultra-high performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) was developed to accurately detect toripalimab levels, compared with the ECLIA. Plasma samples were pretreated by a five-step process, encompassing denaturation, reduction, alkylation, enzymatic hydrolysis and quenching. And a unique, sensitive and stable enzymatic peptide (ASGYTFTDYEMHWVR) selected as surrogate of toripalimab was eluted and monitored by UPLC-MS/MS system with the linear range of 5.0375-201.5 µg/mL. After fully validated, the UPLC-MS/MS method was applied to determine 77 plasma samples from 29 patients in a phase I clinical trial, and compared with ECLIA based on 56 samples. Wilcoxon paired samples test showed toripalimab levels by UPLC-MS/MS were significantly higher than that by ECLIA (p < 0.001), though a strong correlation was observed (r = 0.96). Moreover, Passing-Bablok regression analysis exhibited constant and proportional biases: UPLC-MS/MS = 2.25 + 1.21 * ECLIA. This discrepancy could be mainly attributed to different forms determined: total mAb for UPLC-MS/MS and free mAb for ECLIA, respectively. As a result, this UPLC-MS/MS method may be complementary to ECLIA to monitor different forms of toripalimab. Beyond that, it can be easily modified to simultaneously quantitate multiple-analyte with a small volume of plasma.

SLF1 polymorphism predicts response to oxaliplatin-based adjuvant chemotherapy in patients with colon cancer.

Response to oxaliplatin-based adjuvant chemotherapy varies among patients with stage II and III colon cancer; however, genetic alterations associated with this response remain incompletely characterized. A three-stage analytical framework, including the discovery, validation, and replication stages, was designed to explore genetic alterations modulating response to oxaliplatin-based chemotherapy in adjuvant setting among patients with stage II and III colon cancer receiving complete resection of tumor. Except for several somatic mutated genes, such as ARSD and ACE, showing less definitive associations with response to oxaliplatin-based adjuvant chemotherapy, we found stable associations of rs6891545C > A polymorphism in SLF1 gene, a key component of DNA damage response system, with the response across all three stages. Patients with rs6891545 A allele had significantly lower risk of poor responsiveness to oxaliplatin-based adjuvant chemotherapy at both discovery and validation stages, compared with ones possessing wild homozygous genotype CC (discovery stage: odds ratio, 0; 95% CI, 0-0.48; P = .005; validation stage: odds ratio, 0.33; 95% CI, 0.11-0.99; P = .048). In the replication cohort, rs6891545 A allele was confirmed to be strongly associated with improved DFS (hazard ratio, 0.43; 95% CI, 0.23-0.81; P = .007). Notably, the improvement persisted after controlling for sex, age, tumor location, differentiation, and stage (hazard ratio, 0.42; 95% CI, 0.22-0.80; P = .009). Moreover, in silico analysis unraveled strong impact of rs6891545 A allele on local secondary structure of SLF1 mRNA, possibly leading to low SLF1 protein expression. We conclude that the rs6891545C > A polymorphism may serve as an independent marker of response to oxaliplatin-based adjuvant chemotherapy in patients with stage II and III colon cancer, with improved clinical benefit observed in patients with the A allele possibly attributable to low expression of SLF1 protein resulting in deficient DNA repair capacity.

Autoantibody profiling identifies predictive biomarkers of response to anti-PD1 therapy in cancer patients.

Background: Programmed cell death protein 1 (PD1) inhibitors have revolutionized cancer therapy, yet many patients fail to respond. Thus, the identification of accurate predictive biomarkers of therapy response will improve the clinical benefit of anti-PD1 therapy. Method: We assessed the baseline serological autoantibody (AAb) profile against ~2300 proteins in 10 samples and ~4600 proteins in 35 samples with alveolar soft part sarcoma (ASPS), non-small-cell lung cancer (NSCLC) and lymphoma using Nucleic Acid Programmable Protein Arrays (NAPPA). 23 selected potential AAb biomarkers were verified using simple, affordable and rapid enzyme linked immune sorbent assay (ELISA) technology with baseline plasma samples from 12 ASPS, 16 NSCLC and 46 lymphoma patients. SIX2 and EIF4E2 AAbs were further validated in independent cohorts of 17 NSCLC and 43 lymphoma patients, respectively, using ELISA. The IgG subtypes in response to therapy were also investigated. Results: Distinct AAb profiles between ASPS, NSCLC and lymphoma were observed. In ASPS, the production of P53 and PD1 AAbs were significantly increased in non-responders (p=0.037). In NSCLC, the SIX2 AAb was predictive of response with area under the curve (AUC) of 0.87, 0.85 and 0.90 at 3 months, 4.5 months, 6 months evaluation time points, respectively. In the validation cohort, the SIX2 AAb was consistently up-regulated in non-responders (p=0.024). For lymphoma, the EIF4E2 AAb correlated with a favorable response with AUCs of 0.68, 0.70, and 0.70 at 3 months, 4.5 months, and 6 months, respectively. In the validation cohort, the AUCs were 0.74, 0.75 and 0.66 at 3 months, 4.5 months, and 6 months, respectively. The PD1 and PD-L1 IgG2 AAbs were highly produced in ~20% of lymphoma responders. Furthermore, bioinformatics analysis revealed antigen functions of these AAb biomarkers. Conclusion: This study provides the first evidence that AAb biomarkers selected using high-throughput protein microarrays can predict anti-PD1 therapeutic response and guide anti-PD1 therapy.

CT-707 Overcomes Resistance of Crizotinib through Activating PDPK1- AKT1 Pathway by Targeting FAK.

BACKGROUND: Crizotinib established the position of anaplastic lymphoma kinase-tyrosine kinase inhibitors (ALK-TKI) in the treatment of non-small cell lung cancer (NSCLC) while the therapy- resistance hindered those patients from benefitting continuously from the treatment. CT-707 is an inhibitor of ALK/focal adhesion kinase (FAK) and IGFR-1. H2228CR (crizotinib resistance, CR) and H3122CR NSCLC cell lines were generated from the parental cell line H2228 (EML4-ALK, E6a/b:A20, variant 3) and H3122(EML4-ALK, E13:A20, variant 1), respectively. METHODS: We investigated the antitumor effects CT-707 exerted against H3122CR in vitro /vivo. RESULTS: Importantly, our study provided evidence that CT-707 overcomes resistance to crizotinib through activating PDPK1-AKT1 pathway by targeting FAK. Meanwhile, by using an in-vivo H3122CR xenograft model, we found CT-707 inhibited tumor growth significantly without obvious side effects. CONCLUSION: These findings indicate that CT-707 may be a promising therapeutic agent against crizotinib- resistance in NSCLC.