PO.CL01.22 · 临床研究
联合循环肿瘤细胞和癌症相关巨噬细胞样细胞可增强泛癌种转移性疾病的风险分层模型
Combining circulating tumor cells and cancer associated macrophage-like cells enhances risk stratification models in pan-cancer metastatic disease
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摘要 Abstract
中文摘要
背景：在转移性癌症中，循环肿瘤细胞（CTC）是公认的预后指标，用于识别不太可能对新一线系统治疗产生反应、临床结局较差（如更短的无进展生存期[PFS]和总生存期[OS]）的患者（pts）。然而，CTC通常见于特定恶性肿瘤（乳腺癌、前列腺癌和结肠癌），且往往仅见于<20%的转移性疾病患者，而无CTC的患者也可能快速进展。近期，一种源自肿瘤基质的炎性促肿瘤发生巨噬细胞（即癌症相关巨噬细胞样细胞[CAML]）在>90%的转移性癌症患者中被发现，其吞噬性肿胀似乎与不良结局相关，且独立于CTC。由于CTC和CAML是从单一血液样本中一并分离的，且两者均对结局具有预后价值，我们评估了在6种转移性癌症中于新系统治疗诱导前对二者的应用，以基于2年结局建立患者风险分层模型。
方法：开展了一项前瞻性2年盲法多机构研究，以在新一线系统治疗诱导前对CTC和CAML进行建模来预测结局（n=233），涉及转移性：乳腺癌（n=60）、前列腺癌（n=40）、胰腺癌（n=25）、结肠癌（n=28）、肾细胞癌（RCC）（n=39）和肺癌（n=40）。血液通过CellSieve™滤器过滤，并对CTC亚型和超增大的CAML（≥100μm）进行计数。在该初始数据集上训练机器学习算法以开发预测模型，该模型可根据2年内PFS和OS的可能性对患者群体进行风险分层，并纳入已知的临床变量。
结果：80%（n=185/233）的患者中未检出CTC，其缺失对更好的PFS具有预后价值（HR=1.6，p=0.046），但对OS无预后价值（HR=1.3，p=0.2045）。与此同时，在无CTC的患者中，28%（n=51/185）发现了增大的CAML（≥100μm），且其对更差的PFS（HR=2.0，p=0.0082）和OS（HR=1.9，p=0.0412）也具有预后价值。具体而言，CTC见于55%（n=33）乳腺癌、20%（n=8）前列腺癌、12%（n=3）胰腺癌、11%（n=3）结肠癌、0%（n=0）RCC和0%（n=0）肺癌患者。增大的CAML见于45%（n=27）乳腺癌、20%（n=8）前列腺癌、44%（n=11）胰腺癌、44%（n=17）结肠癌、18%（n=7）RCC和20%（n=8）肺癌患者。总体而言，模型表明≥1个CTC（n=47）的mPFS=3.9且mOS=14.9，而0个CTC且CAML≥100μm的患者（n=51）mPFS=6.9且mOS=13.8，0个CTC且CAML<100μm的患者（n=134）mPFS=10.7且mOS>24个月。
结论：这些初始模型证实CTC和增大的CAML均为更差PFS和OS的预后指标。同时定量CTC和CAML可在多种癌症患者群体中实现更准确的泛癌种风险分层。将更多临床变量纳入模型可能有助于更好的风险亚型划分，并有可能预测最佳治疗方案。
查看英文原文 English abstract
Background: In metastatic cancer, Circulating Tumor cells (CTCs) are established prognostic indictors of patients (pts) less likely to respond to new lines of systemic therapy, with poor clinical outcomes, such as shorter progression free survival (PFS) and overall survival (OS). However, CTCs are typically found in specific malignancies (breast, prostate & colon), often in <20% of pts with metastatic disease, and pts without CTCs may also rapidly progress. Recently, an inflammatory pro-tumorigenic macrophage emanating from tumor stroma (i.e. Cancer associated macrophage-like cell [CAML]) was found in >90% of metastatic cancer pts, and whose phagocytic engorgement appears to correlate with poor outcomes, independent of CTCs. As CTCs and CAMLs are isolated in conjunction from a single blood sample, and both are prognostic for outcomes, we evaluated their utilization prior to induction of new systemic therapy in 6 types of metastatic cancer to model pt risk stratification based on 2 year outcomes.
Methods: A prospective 2 year blind multi-institutional study was undertaken to model CTCs and CAMLs in prognosticating outcomes prior to induction of a new line of systemic therapy (n=233) in metastatic: Breast (n=60), Prostate (n=40), Pancreas (n=25), Colon (n=28), Renal Cell Carcinoma (RCC) (n=39), and Lung (n=40). Blood was filtered by CellSieve TM filters with subtypes of CTCs & hyper-enlarged CAMLs (≥100µm) enumerated. A machine learning algorithm was trained on this initial data set to develop predictive models which could stratify pt populations by risk for likelihood of PFS & OS over 2 years, including known clinical variables.
Results: CTCs were absent in 80% (n=185/233) of pts, and their absence was prognostic for better PFS (HR=1.6, p=0.046), but not OS (HR=1.3, p=0.2045). In parallel, enlarged CAMLs (≥100µm) were found in 28% (n=51/185) of pts without CTCs, and were also prognostic for worse PFS (HR=2.0, p=0.0082) and OS (HR=1.9, p=0.0412). Specifically, CTCs were found in 55% (n=33) breast, 20% (n=8) prostate, 12% (n=3) pancreas, 11% (n=3) colon, 0% (n=0) RCC, and 0% (n=0) lung pts. Enlarged CAMLs were found in 45% (n=27) breast, 20% (n=8) prostate, 44% (n=11) pancreas, 44% (n=17) colon, 18% (n=7) RCC and 20% (n=8) lung pts. Overall, models indicated that ≥1 CTC (n=47) had mPFS=3.9 & mOS=14.9, while pts with 0 CTCs and ≥100µm CAMLs (n=51) had a mPFS=6.9 & mOS=13.8, and pts with 0 CTCs and <100µm CAMLs (n=134) had a mPFS=10.7 & mOS>24 months.
Conclusions: These initial models confirm that both CTCs and enlarged CAMLs are prognostic indicators of worse PFS & OS. The simultaneous quantification both CTCs and CAMLs allows for more accurate pan-cancer risk stratification in an array of cancer pt populations. Additional clinical variables incorporated into the models may allow better risk subtyping and possibly forecast optimal treatment regimens.
利益披露 Disclosure
D. L. Adams,
Creatv Microtech Employment, Stock, Travel, Patent.
S. H. Lin,
SEEK Diagnostics Stock, Other Business Ownership.
AstraZeneca/MedImmune; Other, Honoraria.
Nektar ).
STCube Pharmaceuticals ).
M. Cristofanilli,
Foundation Medicine ).
Pfizer Other, honoraria.
AstraZeneca/Daiichi Sankyo Other, Consultant.
Ellipses Pharma Other, Consultant.
Lilly ).
Angle ).
Merck ).
Olaris Other, Consultant.
Menarini Other, Consultant.
C. Reduzzi,
Menarini Silicon Biosystems ).
S. Chumsri,
AstraZeneca/Daiichi Sankyo Other, consultant.
Athenex Other, consultant.
bioTheranostics Other, consultant.
Eisai Other, consultant.
Immunomedics Other, consultant.
Novartis ), Other, consultant.
Puma Biotechnology Other, consultant.
Syndax Other, consultant.
Merck ).
Pfizer ).
Salix Pharmaceuticals ).
Rebiotix Inc. ).
Athenex Other, consultant.
Briacell Therapeutics ).
Seagen Other, consultant.
Genentech Other, consultant.
Menarini Stemline. Other, consultant.
Axiom. Other, consultant.
Cardinal Health Other, consultant.
S. Tsai, None..
R. C. Bergan, None..
M. Aldakkak, None..
T. H. Ho, None.
C. Tang,
Creatv MicroTech, Inc. Employment, g., Board of Directors, non-salaried role), Stock, Travel, Patent, Trademark, Copyright.