Cancer-associated fibroblasts (CAFs) in thyroid papillary carcinoma: molecular networks and interactions

FAPI PET/CT provides higher uptake and better target to back ground in recurrent and metastatic tumors of patients with Iodine refractory papillary thyroid cancer compared with FDG PET CT

PURPOSE

The role of fibroblast activation protein inhibitor (FAPI) PET CT scan is not well documented in papillary thyroid cancer (PTC) patients. Patients with radioiodine refractory PTC and high thyroglobulin levels need PET/CT scan which is generally done by 18F FDG. In the current study, the diagnostic performance of 68Ga FAPI and FDG PET/CT scans were compared head to head in patients with radioiodine refractory PTC.

METHOD

Fourteen patients with negative whole body Iodine scans and high thyroglobulin levels underwent whole body PET scans with, respectively, 120-310 and 145-370 MBq 68Ga FAPI-46 and 18F FDG. SUVmax of the back ground in the blood pool and liver and the hottest, largest and average neck, mediastinum, lung and bone lesions were calculated and compared.

RESULT

Ten patients had at least one active (SUVmax>blood pool) lesion similarly in two scans. The liver and blood pool SUVmax values were 1.25(0.2) and 1.7(0.2) in FAPI and 2.65(0.2) and 2.0(0.2) in FDG PET images, respectively. The difference was significant (p=0.001). Standard SUV of the hottest lesion to liver was above 3 in all FAPI scans but in half of FDG scans. Target lesion number and intensity were similar between two PET studies but in a patient out of 5 pulmonary metastatic patients, pulmonary nodules were negative (SUVmax=0.9) in FDG while positive (SUVmax= 3.8) in FAPI images (i.e. 20% patient upstaged).

CONCLUSION

FAPI accumulates in the recurrent and metastatic lesions of patients with Iodine refractory PTC at least as well as FDG with particular privileges as lower injected activity and lower back ground.

[18F]FAPI-42 PET/CT in differentiated thyroid cancer: diagnostic performance, uptake values, and comparison with 2-[18F]FDG PET/CT

PURPOSE

This study aimed to assess the diagnostic performance of [¹⁸F]FAPI-42 PET/CT and compare it with that of 2-[¹⁸F]FDG PET/CT in patients with differentiated thyroid cancer (DTC) with biochemical elevations in Tg or anti-Tg antibodies.

METHODS

A total of 42 patients with DTC with biochemical elevations in Tg or anti-Tg antibodies underwent [¹⁸F]FAPI-42 PET/CT as part of this study; of which, 11 additionally underwent 2-[¹⁸F]FDG PET/CT within 7 days. Images were semi-quantitatively and visually interpreted, and the quantity, location, and uptake values of lesions were noted. The diagnostic capacity of [¹⁸F]FAPI-42 PET/CT and biomarkers affecting the uptake of [¹⁸F]FAPI-42 were evaluated. In addition, the diagnostic performance and uptake of [¹⁸F]FAPI-42 and 2-[¹⁸F]FDG were compared, and the correlation between lesion diameter and quantitative parameters was investigated.

RESULTS

A total of 161 lesions were detected in 27 (64%) patients on [¹⁸F]FAPI-42 PET/CT. FAPI-positive local recurrence showed the highest uptake intensity, followed by lymphatic, other site-associated (bone and pleura), and pulmonary lesions (mean SUV_max, 4.7 versus 3.7 versus 3.0 versus 2.2, respectively; P < 0.0001). The levels of TSH, Tg, and Tg-Ab did not affect the uptake value of lesions (median SUV_max: 2.4 versus 3.2, P = 0.56; 2.9 versus 2.4, P = 0.0935; 2.8 versus 2.6, P = 0.0525, respectively). A total of 90 positive lesions were detected in 7 patients using both modalities. All positive lesions showed statistically higher uptake of 2-[¹⁸F]FDG than that of [¹⁸F]FAPI-42 (SUV_max, 2.6 versus 2.1; P = 0.026). However, the SUV_max of [¹⁸F]FAPI-42 was higher than that of 2-[¹⁸F]FDG in local recurrences and lymphatic lesions (SUV_max, 4.2 versus 2.9 and 3.9 versus 3.4, respectively; P > 0.05).

CONCLUSION

[¹⁸F]FAPI-42 can be used for detecting lesions and reflecting FAP expression during local recurrence and metastasis in patients with DTC with biochemical elevations in Tg or anti-Tg antibodies. The diagnostic performance of [¹⁸F]FAPI-42 PET/CT is comparable with that of 2-[¹⁸F]FDG PET/CT in such patients.

Machine learning identifies characteristics molecules of cancer associated fibroblasts significantly correlated with the prognosis, immunotherapy response and immune microenvironment in lung adenocarcinoma

BACKGROUND

Lung adenocarcinoma (LUAD) is a highly lethal disease with a dramatic pro-fibrocytic response. Cancer-associated fibroblasts (CAFs) have been reported to play a key role in lung adenocarcinoma.

METHODS

Marker genes of CAFs were obtained from the Cell Marker website. Single sample gene set enrichment analysis (ssGSEA) was used for CAFs quantification. R and GraphPad Prism software were utilized for all analysis. Quantitative real-time PCR (qRT-PCR) was utilized to detect the RNA level of specific molecules.

RESULTS

Based on the ssGSEA algorithm and obtained CAFs markers, the LUAD patients with low- and high-CAFs infiltration were successfully identified, which had different response patterns to immunotherapy. Through the machine learning algorithm - LASSO logistic regression, we identified 44 characteristic molecules of CAFs. Furthermore, a prognosis signature consisting of seven characteristic genes was established, which showed great prognosis prediction ability. Additionally, we found that patients in the low-risk group might have better outcomes when receiving immunotherapy of PD-1, but not CTLA4. Also, the biological enrichment analysis revealed that immune response-related pathways were significantly associated with CAFs infiltration. Meanwhile, we investigated the underlying biological and microenvironment difference in patients with high- and low-risk groups. Finally, we identified that AMPD1 might be a novel target for LUAD immunotherapy. Patients with a high level of AMPD1 were correlated with worse responses to immunotherapy. Moreover, immunohistochemistry showed that the protein level of AMPD1 was higher in lung cancer. Results of qRT-PCR demonstrated that AMPD1 was upregulated in A549 cells compared with BEAS-2B. Meanwhile, we found that the knockdown of AMPD4 can significantly reduce the expression of CTLA4 and PDCD1, but not CD274 and PDCD1LG2.

CONCLUSION

We comprehensively explored the role of CAFs and its characteristics molecules in LUAD immunotherapy and developed an effective signature to indicate patients prognosis and immunotherapy response. Moreover, AMPD1 was identified as a novel target for lung cancer immunotherapy.

Single-Cell Transcriptomic Analysis of Ecosystems in Papillary Thyroid Carcinoma Progression

BACKGROUND

Despite extensive research, the papillary thyroid carcinoma (PTC) ecosystem is poorly characterized and, in particular, locoregional progression. Available evidence supports that single-cell transcriptome sequencing (Sc-RNA seq) can dissect tumor ecosystems.

METHODS

Tissue samples from one PTC patient, including matched primary tumor (Ca), lymph node (LN) metastasis, and paracancerous tissue (PCa), were subjected to Sc-RNA seq with 10×Genomics. Dual-label immunofluorescence and immunohistochemistry were used to confirm the existence of cell subtypes in a separate cohort.

RESULTS

11,805 cell transcriptomes were profiled, cell landscapes of PTC were composed of malignant follicular epithelial cells (MFECs), CD8⁺ and CD4⁺ T cells, B cells, vascular endothelial cells, fibroblasts and cancer-associated fibroblasts (CAFs). Between Ca and LN ecosystems, the proportions of MFEC and interstitial cells were similar, less than 1/25(229/6,694, 361/3,895), while the proportion of normal follicular epithelial cells (NFECs) and interstitial cells was > 2 in PCa (455/171). NFECs in PCa formed a separate cluster, while MFECs in Ca and LN exhibited a profound transcriptional overlap, and the interstitial cells among these samples had an overall concordance in their identity and representation, albeit with some distinctions in terms of the cell percentage per subset. A fraction of the B cell subpopulation in Ca expressed inhibitory receptors, while their respective ligand genes were clearly transcribed in T cell and malignant epithelial cell clusters, while some CD8⁺ T cells in both Ca and LN produced high levels of inhibitory receptors whose respective ligands were overexpressed in some CD4⁺ T cells. Three CAF subtypes in Ca and LN were identified, which may be due to mutual transitions.

CONCLUSIONS

Our data provide new insights into the PTC ecosystem and highlight the differences in ecosystems in PTC progression, which updates our understanding of PTC biology and will improve individualized patient treatment.