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Clinical trials frequently include multiple end points that mature at different times. The initial report, typically based on the primary end point, may be published when key planned co-primary or secondary analyses are not yet available. Clinical Trial Updates provide an opportunity to disseminate additional results from studies, published in JCO or elsewhere, for which the primary end point has already been reported. We analyzed long-term results of the response-adapted trial for adult patients with advanced-stage Hodgkin lymphoma. The aim was to confirm noninferiority of treatment de-escalation by omission of bleomycin from doxorubicin, bleomycin, vinblastine, and dacarbazine (ABVD) for interim fluorodeoxyglucose positron emission tomography (iPET)–negative patients and assess efficacy and long-term safety for iPET-positive patients who underwent treatment intensification with escalated bleomycin, etoposide, doxorubicin, cyclophosphamide, vincristine, procarbazine, and prednisolone (BEACOPP/BEACOPP14). The median follow-up is 7.3 years. For all patients, the 7-year progression-free survival (PFS) and overall survival (OS) are 78.2% (95% CI, 75.6 to 80.5) and 91.6% (95% CI, 89.7 to 93.2), respectively. The 1.3% difference in 3-year PFS (95% CI, –3.0 to 4.7) between ABVD and doxorubicin, vinblastine, and dacarbazine (AVD) now falls within the predefined noninferiority margin. Among 172 patients with positive iPET, the 7-year PFS was 65.9% (95% CI, 58.1 to 72.6) and the 7-year OS was 83.2% (95% CI, 76.2 to 88.3). The cumulative incidence of second malignancies at 7 years was 5.5% (95% CI, 4.0 to 7.5) for those receiving ABVD/AVD and 2.5% (95% CI, 0.8 to 7.7) for those escalated to BEACOPP. With extended follow-up, these results confirm noninferiority of treatment de-escalation after a negative iPET. Escalation with BEACOPP for iPET-positive patients is effective and safe, with no increase in second malignancies.

Clinical trials frequently include multiple end points that mature at different times. The initial report, typically based on the primary end point, may be published when key planned co-primary or secondary analyses are not yet available. Clinical Trial Updates provide an opportunity to disseminate additional results from studies, published in JCO or elsewhere, for which the primary end point has already been reported. We analyzed long-term results of the response-adapted trial for adult patients with advanced-stage Hodgkin lymphoma. The aim was to confirm noninferiority of treatment de-escalation by omission of bleomycin from doxorubicin, bleomycin, vinblastine, and dacarbazine (ABVD) for interim fluorodeoxyglucose positron emission tomography (iPET)–negative patients and assess efficacy and long-term safety for iPET-positive patients who underwent treatment intensification with escalated bleomycin, etoposide, doxorubicin, cyclophosphamide, vincristine, procarbazine, and prednisolone (BEACOPP/BEACOPP14). The median follow-up is 7.3 years. For all patients, the 7-year progression-free survival (PFS) and overall survival (OS) are 78.2% (95% CI, 75.6 to 80.5) and 91.6% (95% CI, 89.7 to 93.2), respectively. The 1.3% difference in 3-year PFS (95% CI, –3.0 to 4.7) between ABVD and doxorubicin, vinblastine, and dacarbazine (AVD) now falls within the predefined noninferiority margin. Among 172 patients with positive iPET, the 7-year PFS was 65.9% (95% CI, 58.1 to 72.6) and the 7-year OS was 83.2% (95% CI, 76.2 to 88.3). The cumulative incidence of second malignancies at 7 years was 5.5% (95% CI, 4.0 to 7.5) for those receiving ABVD/AVD and 2.5% (95% CI, 0.8 to 7.7) for those escalated to BEACOPP. With extended follow-up, these results confirm noninferiority of treatment de-escalation after a negative iPET. Escalation with BEACOPP for iPET-positive patients is effective and safe, with no increase in second malignancies.

Clinical trials frequently include multiple end points that mature at different times. The initial report, typically based on the primary end point, may be published when key planned co-primary or secondary analyses are not yet available. Clinical Trial Updates provide an opportunity to disseminate additional results from studies, published in JCO or elsewhere, for which the primary end point has already been reported. We analyzed long-term results of the response-adapted trial for adult patients with advanced-stage Hodgkin lymphoma. The aim was to confirm noninferiority of treatment de-escalation by omission of bleomycin from doxorubicin, bleomycin, vinblastine, and dacarbazine (ABVD) for interim fluorodeoxyglucose positron emission tomography (iPET)–negative patients and assess efficacy and long-term safety for iPET-positive patients who underwent treatment intensification with escalated bleomycin, etoposide, doxorubicin, cyclophosphamide, vincristine, procarbazine, and prednisolone (BEACOPP/BEACOPP14). The median follow-up is 7.3 years. For all patients, the 7-year progression-free survival (PFS) and overall survival (OS) are 78.2% (95% CI, 75.6 to 80.5) and 91.6% (95% CI, 89.7 to 93.2), respectively. The 1.3% difference in 3-year PFS (95% CI, –3.0 to 4.7) between ABVD and doxorubicin, vinblastine, and dacarbazine (AVD) now falls within the predefined noninferiority margin. Among 172 patients with positive iPET, the 7-year PFS was 65.9% (95% CI, 58.1 to 72.6) and the 7-year OS was 83.2% (95% CI, 76.2 to 88.3). The cumulative incidence of second malignancies at 7 years was 5.5% (95% CI, 4.0 to 7.5) for those receiving ABVD/AVD and 2.5% (95% CI, 0.8 to 7.7) for those escalated to BEACOPP. With extended follow-up, these results confirm noninferiority of treatment de-escalation after a negative iPET. Escalation with BEACOPP for iPET-positive patients is effective and safe, with no increase in second malignancies.

Clinical trials frequently include multiple end points that mature at different times. The initial report, typically based on the primary end point, may be published when key planned co-primary or secondary analyses are not yet available. Clinical Trial Updates provide an opportunity to disseminate additional results from studies, published in JCO or elsewhere, for which the primary end point has already been reported. We analyzed long-term results of the response-adapted trial for adult patients with advanced-stage Hodgkin lymphoma. The aim was to confirm noninferiority of treatment de-escalation by omission of bleomycin from doxorubicin, bleomycin, vinblastine, and dacarbazine (ABVD) for interim fluorodeoxyglucose positron emission tomography (iPET)–negative patients and assess efficacy and long-term safety for iPET-positive patients who underwent treatment intensification with escalated bleomycin, etoposide, doxorubicin, cyclophosphamide, vincristine, procarbazine, and prednisolone (BEACOPP/BEACOPP14). The median follow-up is 7.3 years. For all patients, the 7-year progression-free survival (PFS) and overall survival (OS) are 78.2% (95% CI, 75.6 to 80.5) and 91.6% (95% CI, 89.7 to 93.2), respectively. The 1.3% difference in 3-year PFS (95% CI, –3.0 to 4.7) between ABVD and doxorubicin, vinblastine, and dacarbazine (AVD) now falls within the predefined noninferiority margin. Among 172 patients with positive iPET, the 7-year PFS was 65.9% (95% CI, 58.1 to 72.6) and the 7-year OS was 83.2% (95% CI, 76.2 to 88.3). The cumulative incidence of second malignancies at 7 years was 5.5% (95% CI, 4.0 to 7.5) for those receiving ABVD/AVD and 2.5% (95% CI, 0.8 to 7.7) for those escalated to BEACOPP. With extended follow-up, these results confirm noninferiority of treatment de-escalation after a negative iPET. Escalation with BEACOPP for iPET-positive patients is effective and safe, with no increase in second malignancies.

Background and purpose: The Swedish Lymphoma Register (SLR) was initiated in the year 2000 with the aim to monitor quality of care in diagnostics, treatment and outcome of all lymphomas diagnosed nationally among adults. Here, we present the first systematic validation of SLR records as a basis for improved register quality and patient care. Patients and methods: We evaluated timeliness and completeness of register records among patients diagnosed with lymphoma in the SLR (n n = 16,905) compared with the National Cancer Register for the period 2013-2020. Comparability was assessed through evaluation of coding routines against national and international guidelines. Accuracy of 42 variables was evaluated through re-abstraction of data from medical records among 600 randomly selected patients diagnosed in 2016-2017 and treated across all six Swedish healthcare regions. Results: Completeness was high, >95% per year for the period 2013-2018, and >89% for 2019-2020 compared to the National Cancer Register. One in four patients was registered within 3 months, and 89.9% within 2 years of diagnosis. Registration instructions and coding procedures followed the prespecified guidelines. Missingness was generally low (<5%), but high for occasional variables, for example, those describing maintenance and consolidative treatment. Exact agreement of categorical variables was high overall (>80% for 24/34 variables), especially for treatment-related data (>80% for 17/19 variables). Interpretation: Completeness and accuracy are high in the SLR, while timeliness could be improved. Finetuning of variable registration guided by this validation can further improve reliability of register reports and advance service to lymphoma patients and health care in the future.

Validation of biobanks and large cancer cohorts is essential in ensuring high-quality research results. We examined the coverage, generalisability and validity of the lymphoma collection of the Uppsala-Umeå Comprehensive Cancer Consortium (U-CAN) biobank in Sweden, one of the largest cancer biobanks in Europe. Up until 2022, 889 lymphoma patients in U-CAN Uppsala had available samples, and 329 in U-CAN Umeå. Patients diagnosed in the U-CAN Uppsala area 2011–2021 (n = 843) were linked to the nationwide Swedish Lymphoma Register, and a subset diagnosed before 2019 (n = 727) to population-based registers. The coverage was 39% of all lymphoma patients between 2011 and 2019 diagnosed in the U-CAN Uppsala area, with a pandemic decline to 10% during 2020–2021. The patients included had superior overall survival (hazard ratio = 0.70 [95% confidence interval, CI: 0.60–0.82]) than all lymphoma patients in Sweden. They had better performance status, were younger (odds ratio [OR] = 0.21 [95% CI: 0.13–0.34]) and had less comorbidities (OR = 0.66 [95% CI: 0.56–0.78]). However, cause-specific survival and stage distribution were similar. The questionnaire data captured less comorbidities compared to the national registers. Evaluations of biobanks are important, as even population-based biobanks such as U-CAN select younger patients with higher socioeconomical status and better performance status. However, the similar cause-specific survival as in the registries suggests U-CANs usefulness for prognostic biomarker studies.

Background and purpose: The Swedish Lymphoma Register (SLR) was initiated in the year 2000 with the aim to monitor quality of care in diagnostics, treatment and outcome of all lymphomas diagnosed nationally among adults. Here, we present the first systematic validation of SLR records as a basis for improved register quality and patient care. Patients and methods: We evaluated timeliness and completeness of register records among patients diagnosed with lymphoma in the SLR (n n = 16,905) compared with the National Cancer Register for the period 2013-2020. Comparability was assessed through evaluation of coding routines against national and international guidelines. Accuracy of 42 variables was evaluated through re-abstraction of data from medical records among 600 randomly selected patients diagnosed in 2016-2017 and treated across all six Swedish healthcare regions. Results: Completeness was high, >95% per year for the period 2013-2018, and >89% for 2019-2020 compared to the National Cancer Register. One in four patients was registered within 3 months, and 89.9% within 2 years of diagnosis. Registration instructions and coding procedures followed the prespecified guidelines. Missingness was generally low (<5%), but high for occasional variables, for example, those describing maintenance and consolidative treatment. Exact agreement of categorical variables was high overall (>80% for 24/34 variables), especially for treatment-related data (>80% for 17/19 variables). Interpretation: Completeness and accuracy are high in the SLR, while timeliness could be improved. Finetuning of variable registration guided by this validation can further improve reliability of register reports and advance service to lymphoma patients and health care in the future.

Despite the improvements in clinical outcomes for DLBCL, a significant proportion of patients still face challenges with refractory/relapsed (R/R) disease after receiving first-line R-CHOP treatment. To further elucidate the underlying mechanism of R/R disease and to develop methods for identifying patients at risk of early disease progression, we integrated clinical, genetic and transcriptomic data derived from 2805 R-CHOP-treated patients from seven independent cohorts. Among these, 887 patients exhibited R/R disease within two years (poor outcome), and 1918 patients remained in remission at two years (good outcome). Our analysis identified four preferentially mutated genes (TP53, MYD88, SPEN, MYC) in the untreated (diagnostic) tumor samples from patients with poor outcomes. Furthermore, transcriptomic analysis revealed a distinct gene expression pattern linked to poor outcomes, affecting pathways involved in cell adhesion/migration, T-cell activation/regulation, PI3K, and NF-kappa B signaling. Moreover, we developed and validated a 24-gene expression score as an independent prognostic predictor for treatment outcomes. This score also demonstrated efficacy in further stratifying high-risk patients when integrated with existing genetic or cell-of-origin subtypes, including the unclassified cases in these models. Finally, based on these findings, we developed an online analysis tool (https://lymphprog.serve.scilifelab.se/app/lymphprog) that can be used for prognostic prediction for DLBCL patients.

Early cancer detection, guided by whole-body imaging, is important for the overall survival and well-being of the patients. While various computer-assisted systems have been developed to expedite and enhance cancer diagnostics and longitudinal monitoring, the detection and segmentation of tumors, especially from whole-body scans, remain challenging. To address this, we propose a novel end -to-end automated framework that first generates a tumor probability distribution map (TPDM), incorporating prior information about the tumor characteristics (e.g. size, shape, location). Subsequently, the TPDM is integrated with a state-of-the-art 3D segmentation network along with the original PET/CT or PET/MR images. This aims to produce more meaningful tumor segmentation masks compared to using the baseline 3D segmentation network alone. The proposed method was evaluated on three independent cohorts (autoPET, CAR-T, cHL) of images containing different cancer forms, obtained with different imaging modalities, and acquisition parameters and lesions annotated by different experts. The evaluation demonstrated the superiority of our proposed method over the baseline model by significant margins in terms of Dice coefficient, and lesion-wise sensitivity and precision. Many of the extremely small tumor lesions (i.e. the most difficult to segment) were missed by the baseline model but detected by the proposed model without additional false positives, resulting in clinically more relevant assessments. On average, an improvement of 0.0251 (autoPET), 0.144 (CAR-T), and 0.0528 (cHL) in overall Dice was observed. In conclusion, the proposed TPDM-based approach can be integrated with any state-of-the-art 3D UNET with potentially more accurate and robust segmentation results.

Background and purpose: The Swedish Lymphoma Register (SLR) was initiated in the year 2000 with the aim to monitor quality of care in diagnostics, treatment and outcome of all lymphomas diagnosed nationally among adults. Here, we present the first systematic validation of SLR records as a basis for improved register quality and patient care. Patients and methods: We evaluated timeliness and completeness of register records among patients diagnosed with lymphoma in the SLR (n n = 16,905) compared with the National Cancer Register for the period 2013-2020. Comparability was assessed through evaluation of coding routines against national and international guidelines. Accuracy of 42 variables was evaluated through re-abstraction of data from medical records among 600 randomly selected patients diagnosed in 2016-2017 and treated across all six Swedish healthcare regions. Results: Completeness was high, >95% per year for the period 2013-2018, and >89% for 2019-2020 compared to the National Cancer Register. One in four patients was registered within 3 months, and 89.9% within 2 years of diagnosis. Registration instructions and coding procedures followed the prespecified guidelines. Missingness was generally low (<5%), but high for occasional variables, for example, those describing maintenance and consolidative treatment. Exact agreement of categorical variables was high overall (>80% for 24/34 variables), especially for treatment-related data (>80% for 17/19 variables). Interpretation: Completeness and accuracy are high in the SLR, while timeliness could be improved. Finetuning of variable registration guided by this validation can further improve reliability of register reports and advance service to lymphoma patients and health care in the future.

Despite the improvements in clinical outcomes for DLBCL, a significant proportion of patients still face challenges with refractory/relapsed (R/R) disease after receiving first-line R-CHOP treatment. To further elucidate the underlying mechanism of R/R disease and to develop methods for identifying patients at risk of early disease progression, we integrated clinical, genetic and transcriptomic data derived from 2805 R-CHOP-treated patients from seven independent cohorts. Among these, 887 patients exhibited R/R disease within two years (poor outcome), and 1918 patients remained in remission at two years (good outcome). Our analysis identified four preferentially mutated genes (TP53, MYD88, SPEN, MYC) in the untreated (diagnostic) tumor samples from patients with poor outcomes. Furthermore, transcriptomic analysis revealed a distinct gene expression pattern linked to poor outcomes, affecting pathways involved in cell adhesion/migration, T-cell activation/regulation, PI3K, and NF-kappa B signaling. Moreover, we developed and validated a 24-gene expression score as an independent prognostic predictor for treatment outcomes. This score also demonstrated efficacy in further stratifying high-risk patients when integrated with existing genetic or cell-of-origin subtypes, including the unclassified cases in these models. Finally, based on these findings, we developed an online analysis tool (https://lymphprog.serve.scilifelab.se/app/lymphprog) that can be used for prognostic prediction for DLBCL patients.

Early cancer detection, guided by whole-body imaging, is important for the overall survival and well-being of the patients. While various computer-assisted systems have been developed to expedite and enhance cancer diagnostics and longitudinal monitoring, the detection and segmentation of tumors, especially from whole-body scans, remain challenging. To address this, we propose a novel end -to-end automated framework that first generates a tumor probability distribution map (TPDM), incorporating prior information about the tumor characteristics (e.g. size, shape, location). Subsequently, the TPDM is integrated with a state-of-the-art 3D segmentation network along with the original PET/CT or PET/MR images. This aims to produce more meaningful tumor segmentation masks compared to using the baseline 3D segmentation network alone. The proposed method was evaluated on three independent cohorts (autoPET, CAR-T, cHL) of images containing different cancer forms, obtained with different imaging modalities, and acquisition parameters and lesions annotated by different experts. The evaluation demonstrated the superiority of our proposed method over the baseline model by significant margins in terms of Dice coefficient, and lesion-wise sensitivity and precision. Many of the extremely small tumor lesions (i.e. the most difficult to segment) were missed by the baseline model but detected by the proposed model without additional false positives, resulting in clinically more relevant assessments. On average, an improvement of 0.0251 (autoPET), 0.144 (CAR-T), and 0.0528 (cHL) in overall Dice was observed. In conclusion, the proposed TPDM-based approach can be integrated with any state-of-the-art 3D UNET with potentially more accurate and robust segmentation results.

Validation of biobanks and large cancer cohorts is essential in ensuring high-quality research results. We examined the coverage, generalisability and validity of the lymphoma collection of the Uppsala-Umeå Comprehensive Cancer Consortium (U-CAN) biobank in Sweden, one of the largest cancer biobanks in Europe. Up until 2022, 889 lymphoma patients in U-CAN Uppsala had available samples, and 329 in U-CAN Umeå. Patients diagnosed in the U-CAN Uppsala area 2011–2021 (n = 843) were linked to the nationwide Swedish Lymphoma Register, and a subset diagnosed before 2019 (n = 727) to population-based registers. The coverage was 39% of all lymphoma patients between 2011 and 2019 diagnosed in the U-CAN Uppsala area, with a pandemic decline to 10% during 2020–2021. The patients included had superior overall survival (hazard ratio = 0.70 [95% confidence interval, CI: 0.60–0.82]) than all lymphoma patients in Sweden. They had better performance status, were younger (odds ratio [OR] = 0.21 [95% CI: 0.13–0.34]) and had less comorbidities (OR = 0.66 [95% CI: 0.56–0.78]). However, cause-specific survival and stage distribution were similar. The questionnaire data captured less comorbidities compared to the national registers. Evaluations of biobanks are important, as even population-based biobanks such as U-CAN select younger patients with higher socioeconomical status and better performance status. However, the similar cause-specific survival as in the registries suggests U-CANs usefulness for prognostic biomarker studies.

Background and purpose: The Swedish Lymphoma Register (SLR) was initiated in the year 2000 with the aim to monitor quality of care in diagnostics, treatment and outcome of all lymphomas diagnosed nationally among adults. Here, we present the first systematic validation of SLR records as a basis for improved register quality and patient care. Patients and methods: We evaluated timeliness and completeness of register records among patients diagnosed with lymphoma in the SLR (n n = 16,905) compared with the National Cancer Register for the period 2013-2020. Comparability was assessed through evaluation of coding routines against national and international guidelines. Accuracy of 42 variables was evaluated through re-abstraction of data from medical records among 600 randomly selected patients diagnosed in 2016-2017 and treated across all six Swedish healthcare regions. Results: Completeness was high, >95% per year for the period 2013-2018, and >89% for 2019-2020 compared to the National Cancer Register. One in four patients was registered within 3 months, and 89.9% within 2 years of diagnosis. Registration instructions and coding procedures followed the prespecified guidelines. Missingness was generally low (<5%), but high for occasional variables, for example, those describing maintenance and consolidative treatment. Exact agreement of categorical variables was high overall (>80% for 24/34 variables), especially for treatment-related data (>80% for 17/19 variables). Interpretation: Completeness and accuracy are high in the SLR, while timeliness could be improved. Finetuning of variable registration guided by this validation can further improve reliability of register reports and advance service to lymphoma patients and health care in the future.

Despite the improvements in clinical outcomes for DLBCL, a significant proportion of patients still face challenges with refractory/relapsed (R/R) disease after receiving first-line R-CHOP treatment. To further elucidate the underlying mechanism of R/R disease and to develop methods for identifying patients at risk of early disease progression, we integrated clinical, genetic and transcriptomic data derived from 2805 R-CHOP-treated patients from seven independent cohorts. Among these, 887 patients exhibited R/R disease within two years (poor outcome), and 1918 patients remained in remission at two years (good outcome). Our analysis identified four preferentially mutated genes (TP53, MYD88, SPEN, MYC) in the untreated (diagnostic) tumor samples from patients with poor outcomes. Furthermore, transcriptomic analysis revealed a distinct gene expression pattern linked to poor outcomes, affecting pathways involved in cell adhesion/migration, T-cell activation/regulation, PI3K, and NF-kappa B signaling. Moreover, we developed and validated a 24-gene expression score as an independent prognostic predictor for treatment outcomes. This score also demonstrated efficacy in further stratifying high-risk patients when integrated with existing genetic or cell-of-origin subtypes, including the unclassified cases in these models. Finally, based on these findings, we developed an online analysis tool (https://lymphprog.serve.scilifelab.se/app/lymphprog) that can be used for prognostic prediction for DLBCL patients.

Early cancer detection, guided by whole-body imaging, is important for the overall survival and well-being of the patients. While various computer-assisted systems have been developed to expedite and enhance cancer diagnostics and longitudinal monitoring, the detection and segmentation of tumors, especially from whole-body scans, remain challenging. To address this, we propose a novel end -to-end automated framework that first generates a tumor probability distribution map (TPDM), incorporating prior information about the tumor characteristics (e.g. size, shape, location). Subsequently, the TPDM is integrated with a state-of-the-art 3D segmentation network along with the original PET/CT or PET/MR images. This aims to produce more meaningful tumor segmentation masks compared to using the baseline 3D segmentation network alone. The proposed method was evaluated on three independent cohorts (autoPET, CAR-T, cHL) of images containing different cancer forms, obtained with different imaging modalities, and acquisition parameters and lesions annotated by different experts. The evaluation demonstrated the superiority of our proposed method over the baseline model by significant margins in terms of Dice coefficient, and lesion-wise sensitivity and precision. Many of the extremely small tumor lesions (i.e. the most difficult to segment) were missed by the baseline model but detected by the proposed model without additional false positives, resulting in clinically more relevant assessments. On average, an improvement of 0.0251 (autoPET), 0.144 (CAR-T), and 0.0528 (cHL) in overall Dice was observed. In conclusion, the proposed TPDM-based approach can be integrated with any state-of-the-art 3D UNET with potentially more accurate and robust segmentation results.

Background and purpose: The Swedish Lymphoma Register (SLR) was initiated in the year 2000 with the aim to monitor quality of care in diagnostics, treatment and outcome of all lymphomas diagnosed nationally among adults. Here, we present the first systematic validation of SLR records as a basis for improved register quality and patient care. Patients and methods: We evaluated timeliness and completeness of register records among patients diagnosed with lymphoma in the SLR (n n = 16,905) compared with the National Cancer Register for the period 2013-2020. Comparability was assessed through evaluation of coding routines against national and international guidelines. Accuracy of 42 variables was evaluated through re-abstraction of data from medical records among 600 randomly selected patients diagnosed in 2016-2017 and treated across all six Swedish healthcare regions. Results: Completeness was high, >95% per year for the period 2013-2018, and >89% for 2019-2020 compared to the National Cancer Register. One in four patients was registered within 3 months, and 89.9% within 2 years of diagnosis. Registration instructions and coding procedures followed the prespecified guidelines. Missingness was generally low (<5%), but high for occasional variables, for example, those describing maintenance and consolidative treatment. Exact agreement of categorical variables was high overall (>80% for 24/34 variables), especially for treatment-related data (>80% for 17/19 variables). Interpretation: Completeness and accuracy are high in the SLR, while timeliness could be improved. Finetuning of variable registration guided by this validation can further improve reliability of register reports and advance service to lymphoma patients and health care in the future.

Despite the improvements in clinical outcomes for DLBCL, a significant proportion of patients still face challenges with refractory/relapsed (R/R) disease after receiving first-line R-CHOP treatment. To further elucidate the underlying mechanism of R/R disease and to develop methods for identifying patients at risk of early disease progression, we integrated clinical, genetic and transcriptomic data derived from 2805 R-CHOP-treated patients from seven independent cohorts. Among these, 887 patients exhibited R/R disease within two years (poor outcome), and 1918 patients remained in remission at two years (good outcome). Our analysis identified four preferentially mutated genes (TP53, MYD88, SPEN, MYC) in the untreated (diagnostic) tumor samples from patients with poor outcomes. Furthermore, transcriptomic analysis revealed a distinct gene expression pattern linked to poor outcomes, affecting pathways involved in cell adhesion/migration, T-cell activation/regulation, PI3K, and NF-kappa B signaling. Moreover, we developed and validated a 24-gene expression score as an independent prognostic predictor for treatment outcomes. This score also demonstrated efficacy in further stratifying high-risk patients when integrated with existing genetic or cell-of-origin subtypes, including the unclassified cases in these models. Finally, based on these findings, we developed an online analysis tool (https://lymphprog.serve.scilifelab.se/app/lymphprog) that can be used for prognostic prediction for DLBCL patients.

Early cancer detection, guided by whole-body imaging, is important for the overall survival and well-being of the patients. While various computer-assisted systems have been developed to expedite and enhance cancer diagnostics and longitudinal monitoring, the detection and segmentation of tumors, especially from whole-body scans, remain challenging. To address this, we propose a novel end -to-end automated framework that first generates a tumor probability distribution map (TPDM), incorporating prior information about the tumor characteristics (e.g. size, shape, location). Subsequently, the TPDM is integrated with a state-of-the-art 3D segmentation network along with the original PET/CT or PET/MR images. This aims to produce more meaningful tumor segmentation masks compared to using the baseline 3D segmentation network alone. The proposed method was evaluated on three independent cohorts (autoPET, CAR-T, cHL) of images containing different cancer forms, obtained with different imaging modalities, and acquisition parameters and lesions annotated by different experts. The evaluation demonstrated the superiority of our proposed method over the baseline model by significant margins in terms of Dice coefficient, and lesion-wise sensitivity and precision. Many of the extremely small tumor lesions (i.e. the most difficult to segment) were missed by the baseline model but detected by the proposed model without additional false positives, resulting in clinically more relevant assessments. On average, an improvement of 0.0251 (autoPET), 0.144 (CAR-T), and 0.0528 (cHL) in overall Dice was observed. In conclusion, the proposed TPDM-based approach can be integrated with any state-of-the-art 3D UNET with potentially more accurate and robust segmentation results.

Clinical trials frequently include multiple end points that mature at different times. The initial report, typically based on the primary end point, may be published when key planned co-primary or secondary analyses are not yet available. Clinical Trial Updates provide an opportunity to disseminate additional results from studies, published in JCO or elsewhere, for which the primary end point has already been reported. We analyzed long-term results of the response-adapted trial for adult patients with advanced-stage Hodgkin lymphoma. The aim was to confirm noninferiority of treatment de-escalation by omission of bleomycin from doxorubicin, bleomycin, vinblastine, and dacarbazine (ABVD) for interim fluorodeoxyglucose positron emission tomography (iPET)–negative patients and assess efficacy and long-term safety for iPET-positive patients who underwent treatment intensification with escalated bleomycin, etoposide, doxorubicin, cyclophosphamide, vincristine, procarbazine, and prednisolone (BEACOPP/BEACOPP14). The median follow-up is 7.3 years. For all patients, the 7-year progression-free survival (PFS) and overall survival (OS) are 78.2% (95% CI, 75.6 to 80.5) and 91.6% (95% CI, 89.7 to 93.2), respectively. The 1.3% difference in 3-year PFS (95% CI, –3.0 to 4.7) between ABVD and doxorubicin, vinblastine, and dacarbazine (AVD) now falls within the predefined noninferiority margin. Among 172 patients with positive iPET, the 7-year PFS was 65.9% (95% CI, 58.1 to 72.6) and the 7-year OS was 83.2% (95% CI, 76.2 to 88.3). The cumulative incidence of second malignancies at 7 years was 5.5% (95% CI, 4.0 to 7.5) for those receiving ABVD/AVD and 2.5% (95% CI, 0.8 to 7.7) for those escalated to BEACOPP. With extended follow-up, these results confirm noninferiority of treatment de-escalation after a negative iPET. Escalation with BEACOPP for iPET-positive patients is effective and safe, with no increase in second malignancies.

Despite the improvements in clinical outcomes for DLBCL, a significant proportion of patients still face challenges with refractory/relapsed (R/R) disease after receiving first-line R-CHOP treatment. To further elucidate the underlying mechanism of R/R disease and to develop methods for identifying patients at risk of early disease progression, we integrated clinical, genetic and transcriptomic data derived from 2805 R-CHOP-treated patients from seven independent cohorts. Among these, 887 patients exhibited R/R disease within two years (poor outcome), and 1918 patients remained in remission at two years (good outcome). Our analysis identified four preferentially mutated genes (TP53, MYD88, SPEN, MYC) in the untreated (diagnostic) tumor samples from patients with poor outcomes. Furthermore, transcriptomic analysis revealed a distinct gene expression pattern linked to poor outcomes, affecting pathways involved in cell adhesion/migration, T-cell activation/regulation, PI3K, and NF-kappa B signaling. Moreover, we developed and validated a 24-gene expression score as an independent prognostic predictor for treatment outcomes. This score also demonstrated efficacy in further stratifying high-risk patients when integrated with existing genetic or cell-of-origin subtypes, including the unclassified cases in these models. Finally, based on these findings, we developed an online analysis tool (https://lymphprog.serve.scilifelab.se/app/lymphprog) that can be used for prognostic prediction for DLBCL patients.

Early cancer detection, guided by whole-body imaging, is important for the overall survival and well-being of the patients. While various computer-assisted systems have been developed to expedite and enhance cancer diagnostics and longitudinal monitoring, the detection and segmentation of tumors, especially from whole-body scans, remain challenging. To address this, we propose a novel end -to-end automated framework that first generates a tumor probability distribution map (TPDM), incorporating prior information about the tumor characteristics (e.g. size, shape, location). Subsequently, the TPDM is integrated with a state-of-the-art 3D segmentation network along with the original PET/CT or PET/MR images. This aims to produce more meaningful tumor segmentation masks compared to using the baseline 3D segmentation network alone. The proposed method was evaluated on three independent cohorts (autoPET, CAR-T, cHL) of images containing different cancer forms, obtained with different imaging modalities, and acquisition parameters and lesions annotated by different experts. The evaluation demonstrated the superiority of our proposed method over the baseline model by significant margins in terms of Dice coefficient, and lesion-wise sensitivity and precision. Many of the extremely small tumor lesions (i.e. the most difficult to segment) were missed by the baseline model but detected by the proposed model without additional false positives, resulting in clinically more relevant assessments. On average, an improvement of 0.0251 (autoPET), 0.144 (CAR-T), and 0.0528 (cHL) in overall Dice was observed. In conclusion, the proposed TPDM-based approach can be integrated with any state-of-the-art 3D UNET with potentially more accurate and robust segmentation results.

The outcome for patients with mantle cell lymphoma (MCL) has drastically improved with new treatments directed toward the tumor immune microenvironment, where macrophages play an important role. In MCL, the presence of M2 macrophages defined by CD163 expression in diagnostic biopsies has been associated with a worse prognosis. An alternative way to assess the abundance of M2 macrophages is by measuring the level of soluble CD163 in serum (sCD163). We aimed to investigate the prognostic value of sCD163 in 131 patients with MCL. We found that high sCD163 at diagnosis was associated with shorter progression-free survival (PFS) and shorter overall survival (OS) in 81 patients who were newly diagnosed and subsequently treated with chemoimmunotherapy. The same was seen in a cohort of 50 patients with relapsed MCL that were mainly treated within the phase 2 Philemon-trial with rituximab, ibrutinib, and lenalidomide. In patients who were newly diagnosed and had low levels of sCD163, 5-year survival was 97%. There was a moderate correlation between sCD163 and tissue CD163. The association with a poor prognosis was independent of MCL international prognostic index, Ki67, p53 status, and blastoid morphology, as assessed in a multivariable Cox proportional hazards model. In this study, high sCD163 was associated with both shorter PFS and shorter OS, showing that high levels of the M2 macrophage marker sCD163 is an independent negative prognostic factor in MCL, both in the chemoimmunotherapy and ibrutinib/lenalidomide era. In addition, low sCD163 levels identify patients with MCL with a very good prognosis.

Purpose: Although CD19 chimeric antigen receptor T cells (CAR-T) therapy has shown remarkable success in B-cell malignancies, a substantial fraction of patients do not obtain a long-term clinical response. This could be influenced by the quality of the individual CAR-T infusion product. To shed some light on this, clinical outcome was correlated to characteristics of CAR-T infusion products. Patients and Methods: In this phase II study, patients with B-cell lymphoma (n = 23) or leukemia (n = 1) received one or two infusions of third-generation CD19-directed CAR-Ts (2 × 108/m2). The clinical trial was registered at clinicaltrials.gov: NCT03068416. We investigated the transcriptional profile of individual CD19 CAR-T infusion products using targeted single-cell RNA sequencing and multicolor flow cytometry. Results: Two CAR-T infusions were not better than one in the settings used in this study. As for the CAR-T infusion products, we found that effector-like CD8+CAR-Ts with a high polyfunctionality, high cytotoxic and cytokine production profile, and low dysfunctional signature were associated with clinical response. An extended ex vivo expansion time during CAR-T manufacturing negatively influenced the proportion of effector CD8+CAR-Ts in the infusion product. Conclusions: We identified cell-intrinsic characteristics of effector CD8+CAR-Ts correlating with response that could be used as an indicator for clinical outcome. The results in the study also serve as a guide to CAR-T manufacturing practices., De två första författarna delar förstaförfattarskapetDe två sista författarna delar sistaförfattarskapet

Background Swedish recommendations to reduce the risk of COVID-19 relied on each citizen’s own sense of responsibility rather than mandatory lockdowns. We studied how COVID-19-related self-isolation and anxiety correlated to SARS-CoV-2 seropositivity and PCR-positivity in patients with active cancer treatment. Methods In a longitudinal cohort study at Uppsala University Hospital patients and cancer personnel were included between April 1st 2020 to August 1st 2020. Serological testing for SARS-CoV-2 was done every 8–12-weeks until 30 March 2021. Patients completed a survey at inclusion regarding self-reported COVID-19-related anxiety and self-isolation. Results A total of 622 patients [n = 475 with solid malignancies (SM), n = 147 with haematological malignancies (HM)], and 358 healthcare personnel were included. The seropositivity rate was lower for patients than for personnel; 10.5% for SM patients, 6.8% for HM patients, and 16.2% for personnel (p = 0.005). Strict adherence to self-isolation guidelines was reported by 54% of patients but was not associated with a lower risk of becoming seropositive [OR = 1.4 (0.8–2.5), p = 0.2]. High anxiety was expressed by 32% of patients, more often by SM patients than HM patients (34% vs 25% [OR = 1.6 (1.1–2.5, p = 0.03)]). Female gender [OR = 3.5 (2.4–5.2), p < 0.001] and being born outside of Europe [OR = 2.9 (1.4–6.4), p = 0.007] were both associated with high anxiety. Patients reporting high anxiety became seropositive to a similar degree as those with low anxiety [OR = 0.7 (0.3–1.2), p = 0.2]. HM patients with PCR-positive COVID-19 were more likely than SM patients to require oxygen therapy, including non-invasive ventilation/intubation (69% vs. 26%, p = 0.005). Conclusion For Swedish patients on active cancer treatment, high self-assessed COVID-19-related anxiety or strict adherence to self-isolation guidelines were not associated with a lower risk of COVID-19. Patients with HM were less likely to develop serological a

Background: Statistical atlases can provide population-based descriptions of healthy volunteers and/or patients and can be used for region- and voxel-based analysis. This work aims to develop whole-body diffusion atlases of healthy volunteers scanned at 1.5T and 3T. Further aims include evaluating the atlases by establishing whole-body Apparent Diffusion Coefficient (ADC) values of healthy tissues and including healthy tissue deviations in an automated tumour segmentation task. Methods: Multi-station whole-body Diffusion Weighted Imaging (DWI) and water-fat Magnetic Resonance Imaging (MRI) of healthy volunteers (n = 45) were acquired at 1.5T (n = 38) and/or 3T (n = 29), with test-retest imaging for five subjects per scanner. Using deformable image registration, whole-body MRI data was registered and composed into normal atlases. Healthy tissue ADCmean was manually measured for ten tissues, with test-retest percentage Repeatability Coefficient (%RC), and effect of age, sex and scanner assessed. Voxel-wise whole-body analyses using the normal atlases were studied with ADC correlation analyses and an automated tumour segmentation task. For the latter, lymphoma patient MRI scans (n = 40) with and without information about healthy tissue deviations were entered into a 3D U-Net architecture. Results: Sex- and Body Mass Index (BMI)-stratified whole-body high b-value DWI and ADC normal atlases were created at 1.5T and 3T. %RC of healthy tissue ADCmean varied depending on tissue assessed (4-48% at 1.5T, 6-70% at 3T). Scanner differences in ADCmean were visualised in Bland-Altman analyses of dually scanned subjects. Sex differences were measurable for liver, muscle and bone at 1.5T, and muscle at 3T. Volume of Interest (VOI)-based multiple linear regression, and voxel-based correlations in normal atlas space, showed that age and ADC were negatively associated for liver and bone at 1.5T, and positively associated with brain tissue at 1.5T and 3T. Adding voxel-wise information

Background Swedish recommendations to reduce the risk of COVID-19 relied on each citizen’s own sense of responsibility rather than mandatory lockdowns. We studied how COVID-19-related self-isolation and anxiety correlated to SARS-CoV-2 seropositivity and PCR-positivity in patients with active cancer treatment. Methods In a longitudinal cohort study at Uppsala University Hospital patients and cancer personnel were included between April 1st 2020 to August 1st 2020. Serological testing for SARS-CoV-2 was done every 8–12-weeks until 30 March 2021. Patients completed a survey at inclusion regarding self-reported COVID-19-related anxiety and self-isolation. Results A total of 622 patients [n = 475 with solid malignancies (SM), n = 147 with haematological malignancies (HM)], and 358 healthcare personnel were included. The seropositivity rate was lower for patients than for personnel; 10.5% for SM patients, 6.8% for HM patients, and 16.2% for personnel (p = 0.005). Strict adherence to self-isolation guidelines was reported by 54% of patients but was not associated with a lower risk of becoming seropositive [OR = 1.4 (0.8–2.5), p = 0.2]. High anxiety was expressed by 32% of patients, more often by SM patients than HM patients (34% vs 25% [OR = 1.6 (1.1–2.5, p = 0.03)]). Female gender [OR = 3.5 (2.4–5.2), p < 0.001] and being born outside of Europe [OR = 2.9 (1.4–6.4), p = 0.007] were both associated with high anxiety. Patients reporting high anxiety became seropositive to a similar degree as those with low anxiety [OR = 0.7 (0.3–1.2), p = 0.2]. HM patients with PCR-positive COVID-19 were more likely than SM patients to require oxygen therapy, including non-invasive ventilation/intubation (69% vs. 26%, p = 0.005). Conclusion For Swedish patients on active cancer treatment, high self-assessed COVID-19-related anxiety or strict adherence to self-isolation guidelines were not associated with a lower risk of COVID-19. Patients with HM were less likely to develop serological a

Background Swedish recommendations to reduce the risk of COVID-19 relied on each citizen’s own sense of responsibility rather than mandatory lockdowns. We studied how COVID-19-related self-isolation and anxiety correlated to SARS-CoV-2 seropositivity and PCR-positivity in patients with active cancer treatment. Methods In a longitudinal cohort study at Uppsala University Hospital patients and cancer personnel were included between April 1st 2020 to August 1st 2020. Serological testing for SARS-CoV-2 was done every 8–12-weeks until 30 March 2021. Patients completed a survey at inclusion regarding self-reported COVID-19-related anxiety and self-isolation. Results A total of 622 patients [n = 475 with solid malignancies (SM), n = 147 with haematological malignancies (HM)], and 358 healthcare personnel were included. The seropositivity rate was lower for patients than for personnel; 10.5% for SM patients, 6.8% for HM patients, and 16.2% for personnel (p = 0.005). Strict adherence to self-isolation guidelines was reported by 54% of patients but was not associated with a lower risk of becoming seropositive [OR = 1.4 (0.8–2.5), p = 0.2]. High anxiety was expressed by 32% of patients, more often by SM patients than HM patients (34% vs 25% [OR = 1.6 (1.1–2.5, p = 0.03)]). Female gender [OR = 3.5 (2.4–5.2), p < 0.001] and being born outside of Europe [OR = 2.9 (1.4–6.4), p = 0.007] were both associated with high anxiety. Patients reporting high anxiety became seropositive to a similar degree as those with low anxiety [OR = 0.7 (0.3–1.2), p = 0.2]. HM patients with PCR-positive COVID-19 were more likely than SM patients to require oxygen therapy, including non-invasive ventilation/intubation (69% vs. 26%, p = 0.005). Conclusion For Swedish patients on active cancer treatment, high self-assessed COVID-19-related anxiety or strict adherence to self-isolation guidelines were not associated with a lower risk of COVID-19. Patients with HM were less likely to develop serological a

Background: Statistical atlases can provide population-based descriptions of healthy volunteers and/or patients and can be used for region- and voxel-based analysis. This work aims to develop whole-body diffusion atlases of healthy volunteers scanned at 1.5T and 3T. Further aims include evaluating the atlases by establishing whole-body Apparent Diffusion Coefficient (ADC) values of healthy tissues and including healthy tissue deviations in an automated tumour segmentation task. Methods: Multi-station whole-body Diffusion Weighted Imaging (DWI) and water-fat Magnetic Resonance Imaging (MRI) of healthy volunteers (n = 45) were acquired at 1.5T (n = 38) and/or 3T (n = 29), with test-retest imaging for five subjects per scanner. Using deformable image registration, whole-body MRI data was registered and composed into normal atlases. Healthy tissue ADCmean was manually measured for ten tissues, with test-retest percentage Repeatability Coefficient (%RC), and effect of age, sex and scanner assessed. Voxel-wise whole-body analyses using the normal atlases were studied with ADC correlation analyses and an automated tumour segmentation task. For the latter, lymphoma patient MRI scans (n = 40) with and without information about healthy tissue deviations were entered into a 3D U-Net architecture. Results: Sex- and Body Mass Index (BMI)-stratified whole-body high b-value DWI and ADC normal atlases were created at 1.5T and 3T. %RC of healthy tissue ADCmean varied depending on tissue assessed (4-48% at 1.5T, 6-70% at 3T). Scanner differences in ADCmean were visualised in Bland-Altman analyses of dually scanned subjects. Sex differences were measurable for liver, muscle and bone at 1.5T, and muscle at 3T. Volume of Interest (VOI)-based multiple linear regression, and voxel-based correlations in normal atlas space, showed that age and ADC were negatively associated for liver and bone at 1.5T, and positively associated with brain tissue at 1.5T and 3T. Adding voxel-wise information

Background Swedish recommendations to reduce the risk of COVID-19 relied on each citizen’s own sense of responsibility rather than mandatory lockdowns. We studied how COVID-19-related self-isolation and anxiety correlated to SARS-CoV-2 seropositivity and PCR-positivity in patients with active cancer treatment. Methods In a longitudinal cohort study at Uppsala University Hospital patients and cancer personnel were included between April 1st 2020 to August 1st 2020. Serological testing for SARS-CoV-2 was done every 8–12-weeks until 30 March 2021. Patients completed a survey at inclusion regarding self-reported COVID-19-related anxiety and self-isolation. Results A total of 622 patients [n = 475 with solid malignancies (SM), n = 147 with haematological malignancies (HM)], and 358 healthcare personnel were included. The seropositivity rate was lower for patients than for personnel; 10.5% for SM patients, 6.8% for HM patients, and 16.2% for personnel (p = 0.005). Strict adherence to self-isolation guidelines was reported by 54% of patients but was not associated with a lower risk of becoming seropositive [OR = 1.4 (0.8–2.5), p = 0.2]. High anxiety was expressed by 32% of patients, more often by SM patients than HM patients (34% vs 25% [OR = 1.6 (1.1–2.5, p = 0.03)]). Female gender [OR = 3.5 (2.4–5.2), p < 0.001] and being born outside of Europe [OR = 2.9 (1.4–6.4), p = 0.007] were both associated with high anxiety. Patients reporting high anxiety became seropositive to a similar degree as those with low anxiety [OR = 0.7 (0.3–1.2), p = 0.2]. HM patients with PCR-positive COVID-19 were more likely than SM patients to require oxygen therapy, including non-invasive ventilation/intubation (69% vs. 26%, p = 0.005). Conclusion For Swedish patients on active cancer treatment, high self-assessed COVID-19-related anxiety or strict adherence to self-isolation guidelines were not associated with a lower risk of COVID-19. Patients with HM were less likely to develop serological a

Purpose: Although CD19 chimeric antigen receptor T cells (CAR-T) therapy has shown remarkable success in B-cell malignancies, a substantial fraction of patients do not obtain a long-term clinical response. This could be influenced by the quality of the individual CAR-T infusion product. To shed some light on this, clinical outcome was correlated to characteristics of CAR-T infusion products. Patients and Methods: In this phase II study, patients with B-cell lymphoma (n = 23) or leukemia (n = 1) received one or two infusions of third-generation CD19-directed CAR-Ts (2 × 108/m2). The clinical trial was registered at clinicaltrials.gov: NCT03068416. We investigated the transcriptional profile of individual CD19 CAR-T infusion products using targeted single-cell RNA sequencing and multicolor flow cytometry. Results: Two CAR-T infusions were not better than one in the settings used in this study. As for the CAR-T infusion products, we found that effector-like CD8+CAR-Ts with a high polyfunctionality, high cytotoxic and cytokine production profile, and low dysfunctional signature were associated with clinical response. An extended ex vivo expansion time during CAR-T manufacturing negatively influenced the proportion of effector CD8+CAR-Ts in the infusion product. Conclusions: We identified cell-intrinsic characteristics of effector CD8+CAR-Ts correlating with response that could be used as an indicator for clinical outcome. The results in the study also serve as a guide to CAR-T manufacturing practices., De två första författarna delar förstaförfattarskapetDe två sista författarna delar sistaförfattarskapet

Purpose: Although CD19 chimeric antigen receptor T cells (CAR-T) therapy has shown remarkable success in B-cell malignancies, a substantial fraction of patients do not obtain a long-term clinical response. This could be influenced by the quality of the individual CAR-T infusion product. To shed some light on this, clinical outcome was correlated to characteristics of CAR-T infusion products. Patients and Methods: In this phase II study, patients with B-cell lymphoma (n = 23) or leukemia (n = 1) received one or two infusions of third-generation CD19-directed CAR-Ts (2 × 108/m2). The clinical trial was registered at clinicaltrials.gov: NCT03068416. We investigated the transcriptional profile of individual CD19 CAR-T infusion products using targeted single-cell RNA sequencing and multicolor flow cytometry. Results: Two CAR-T infusions were not better than one in the settings used in this study. As for the CAR-T infusion products, we found that effector-like CD8+CAR-Ts with a high polyfunctionality, high cytotoxic and cytokine production profile, and low dysfunctional signature were associated with clinical response. An extended ex vivo expansion time during CAR-T manufacturing negatively influenced the proportion of effector CD8+CAR-Ts in the infusion product. Conclusions: We identified cell-intrinsic characteristics of effector CD8+CAR-Ts correlating with response that could be used as an indicator for clinical outcome. The results in the study also serve as a guide to CAR-T manufacturing practices., De två första författarna delar förstaförfattarskapetDe två sista författarna delar sistaförfattarskapet

Purpose: Although CD19 chimeric antigen receptor T cells (CAR-T) therapy has shown remarkable success in B-cell malignancies, a substantial fraction of patients do not obtain a long-term clinical response. This could be influenced by the quality of the individual CAR-T infusion product. To shed some light on this, clinical outcome was correlated to characteristics of CAR-T infusion products. Patients and Methods: In this phase II study, patients with B-cell lymphoma (n = 23) or leukemia (n = 1) received one or two infusions of third-generation CD19-directed CAR-Ts (2 × 108/m2). The clinical trial was registered at clinicaltrials.gov: NCT03068416. We investigated the transcriptional profile of individual CD19 CAR-T infusion products using targeted single-cell RNA sequencing and multicolor flow cytometry. Results: Two CAR-T infusions were not better than one in the settings used in this study. As for the CAR-T infusion products, we found that effector-like CD8+CAR-Ts with a high polyfunctionality, high cytotoxic and cytokine production profile, and low dysfunctional signature were associated with clinical response. An extended ex vivo expansion time during CAR-T manufacturing negatively influenced the proportion of effector CD8+CAR-Ts in the infusion product. Conclusions: We identified cell-intrinsic characteristics of effector CD8+CAR-Ts correlating with response that could be used as an indicator for clinical outcome. The results in the study also serve as a guide to CAR-T manufacturing practices., De två första författarna delar förstaförfattarskapetDe två sista författarna delar sistaförfattarskapet

In follicular lymphoma (FL), progression of disease <= 24 months (POD24) has emerged as an important prognostic marker for overall survival (OS). We aimed to investigate survival more broadly by timing of progression and treatment in a national population-based setting. We identified 948 stage II-IV indolent FL patients in the Swedish Lymphoma Register diagnosed 2007-2014 who received first-line systemic therapy, followed through 2020. Hazard ratios (HRs) with 95% confidence intervals (CIs) were estimated by first POD at any time during follow-up using Cox regression. OS was predicted by POD using an illness-death model. During a median follow-up of 6.1 years (IQR: 3.5-8.4), 414 patients experienced POD (44%), of which 270 (65%) occurred <= 24 months. POD was represented by a transformation in 15% of cases. Compared to progression-free patients, POD increased all-cause mortality across treatments, but less so among patients treated with rituximab(R)-single (HR = 4.54, 95% CI: 2.76-7.47) than R-chemotherapy (HR = 8.17, 95% CI: 6.09-10.94). The effect of POD was similar following R-CHOP (HR = 8.97, 95% CI: 6.14-13.10) and BR (HR = 10.29, 95% CI: 5.60-18.91). The negative impact of POD on survival remained for progressions up to 5 years after R-chemotherapy, but was restricted to 2 years after R-single. After R-chemotherapy, the 5-year OS conditional on POD occurring at 12, 24, and 60 months was 34%, 46%, and 57% respectively, versus 78%, 82%, and 83% if progression-free. To conclude, POD before but also beyond 24 months is associated with worse survival, illustrating the need for individualized management for optimal care of FL patients.

Simple Summary Females show a favorable sex difference in incidence as well as in survival for many cancer types, so also in lymphoma. The reasons for this are unknown. We have therefore analyzed global gene expression in a large cohort of the most common lymphoma type, diffuse large B-cell lymphoma. We show that many genes are differentially expressed between males and females. Furthermore, the results demonstrate sex-dependent differences in gene expression between DLBCL subtypes. In addition, gene expression differs in pre- vs. postmenopausal women suggesting that estrogen regulation of genes is involved. Thus, estrogens may contribute to the sex and female age differences in incidence and prognosis observed. For most lymphomas, including diffuse large B-cell lymphoma (DLBCL), the male incidence is higher, and the prognosis is worse compared to females. The reasons are unclear; however, epidemiological and experimental data suggest that estrogens are involved. With this in mind, we analyzed gene expression data from a publicly available cohort (EGAD00001003600) of 746 DLBCL samples based on RNA sequencing. We found 1293 genes to be differentially expressed between males and females (adj. p-value < 0.05). Few autosomal genes and pathways showed common sex-regulated expression between germinal center B-cell (GCB) and activated B-cell lymphoma (ABC) DLBCL. Analysis of differentially expressed genes between pre- vs. postmenopausal females identified 208 GCB and 345 ABC genes, with only 5 being shared. When combining the differentially expressed genes between females vs. males and pre- vs. postmenopausal females, nine putative estrogen-regulated genes were identified in ABC DLBCL. Two of them, NR4A2 and MUC5B, showed induced and repressed expression, respectively. Interestingly, NR4A2 has been reported as a tumor suppressor in lymphoma. We show that ABC DLBCL females with a high NR4A2 expression showed better survival. Inversely, MUC5B expression causes a more mali

Background: Statistical atlases can provide population-based descriptions of healthy volunteers and/or patients and can be used for region- and voxel-based analysis. This work aims to develop whole-body diffusion atlases of healthy volunteers scanned at 1.5T and 3T. Further aims include evaluating the atlases by establishing whole-body Apparent Diffusion Coefficient (ADC) values of healthy tissues and including healthy tissue deviations in an automated tumour segmentation task. Methods: Multi-station whole-body Diffusion Weighted Imaging (DWI) and water-fat Magnetic Resonance Imaging (MRI) of healthy volunteers (n = 45) were acquired at 1.5T (n = 38) and/or 3T (n = 29), with test-retest imaging for five subjects per scanner. Using deformable image registration, whole-body MRI data was registered and composed into normal atlases. Healthy tissue ADCmean was manually measured for ten tissues, with test-retest percentage Repeatability Coefficient (%RC), and effect of age, sex and scanner assessed. Voxel-wise whole-body analyses using the normal atlases were studied with ADC correlation analyses and an automated tumour segmentation task. For the latter, lymphoma patient MRI scans (n = 40) with and without information about healthy tissue deviations were entered into a 3D U-Net architecture. Results: Sex- and Body Mass Index (BMI)-stratified whole-body high b-value DWI and ADC normal atlases were created at 1.5T and 3T. %RC of healthy tissue ADCmean varied depending on tissue assessed (4-48% at 1.5T, 6-70% at 3T). Scanner differences in ADCmean were visualised in Bland-Altman analyses of dually scanned subjects. Sex differences were measurable for liver, muscle and bone at 1.5T, and muscle at 3T. Volume of Interest (VOI)-based multiple linear regression, and voxel-based correlations in normal atlas space, showed that age and ADC were negatively associated for liver and bone at 1.5T, and positively associated with brain tissue at 1.5T and 3T. Adding voxel-wise information

Comprehensive and scalable proteomic profiling of plasma samples can improve the screening and diagnosis of cancer patients. Here, the authors use the Olink Proximity Extension Assay technology to characterise the plasma proteomes of 1477 patients across twelve cancer types, and use machine learning to obtain a protein panel for cancer classification. A comprehensive characterization of blood proteome profiles in cancer patients can contribute to a better understanding of the disease etiology, resulting in earlier diagnosis, risk stratification and better monitoring of the different cancer subtypes. Here, we describe the use of next generation protein profiling to explore the proteome signature in blood across patients representing many of the major cancer types. Plasma profiles of 1463 proteins from more than 1400 cancer patients are measured in minute amounts of blood collected at the time of diagnosis and before treatment. An open access Disease Blood Atlas resource allows the exploration of the individual protein profiles in blood collected from the individual cancer patients. We also present studies in which classification models based on machine learning have been used for the identification of a set of proteins associated with each of the analyzed cancers. The implication for cancer precision medicine of next generation plasma profiling is discussed.

Recent transcriptomic-based analysis of diffuse large B cell lymphoma (DLBCL) has highlighted the clinical relevance of LN fibroblast and tumor-infiltrating lymphocyte (TIL) signatures within the tumor microenvironment (TME). However, the immunomodulatory role of fibroblasts in lymphoma remains unclear. Here, by studying human and mouse DLBCL-LNs, we identified the presence of an aberrantly remodeled fibroblastic reticular cell (FRC) network expressing elevated fibroblast activated protein (FAP). RNA-Seq analyses revealed that exposure to DLBCL reprogrammed key immunoregulatory pathways in FRCs, including a switch from homeostatic to inflammatory chemokine expression and elevated antigen-presentation molecules. Functional assays showed that DLBCL-activated FRCs (DLBCL-FRCs) hindered optimal TIL and chimeric antigen receptor (CAR) T cell migration. Moreover, DLBCL-FRCs inhibited CD'+ TIL cytotoxicity in an antigen-specific manner. Notably, the interrogation of patient LNs with imaging mass cytometry identified distinct environments differing in their CD'+ TIL-FRC composition and spatial organization that associated with survival outcomes. We further demonstrated the potential to target inhibitory FRCs to rejuvenate interacting TILs. Cotreating organotypic cultures with FAP-targeted immunostimulatory drugs and a bispecific antibody (glofitamab) augmented antilymphoma TIL cytotoxicity. Our study reveals an immunosuppressive role of FRCs in DLBCL, with implications for immune evasion, disease pathogenesis, and optimizing immunotherapy for patients.

Diffuse large B cell lymphoma (DLBCL) is one of the most common types of aggressive lymphoid malignancies. Here, we explore the contribution of RNA editing to DLBCL pathogenesis. We observed that DNA mutations and RNA editing events are often mutually exclusive, suggesting that tumors can modulate pathway outcomes by altering sequences at either the genomic or the transcriptomic level. RNA editing targets transcripts within known disease-driving pathways such as apoptosis, p53 and NF-kappa B signaling, as well as the RIG-I-like pathway. In this context, we show that ADAR1-mediated editing within MAVS transcript positively correlates with MAVS protein expression levels, associating with increased interferon/NF-kappa B signaling and T cell exhaustion. Finally, using targeted RNA base editing tools to restore editing within MAVS 3 ' UTR in ADAR1-deficient cells, we demonstrate that editing is likely to be causal to an increase in downstream signaling in the absence of activation by canonical nucleic acid receptor sensing.

Simple Summary Females show a favorable sex difference in incidence as well as in survival for many cancer types, so also in lymphoma. The reasons for this are unknown. We have therefore analyzed global gene expression in a large cohort of the most common lymphoma type, diffuse large B-cell lymphoma. We show that many genes are differentially expressed between males and females. Furthermore, the results demonstrate sex-dependent differences in gene expression between DLBCL subtypes. In addition, gene expression differs in pre- vs. postmenopausal women suggesting that estrogen regulation of genes is involved. Thus, estrogens may contribute to the sex and female age differences in incidence and prognosis observed. For most lymphomas, including diffuse large B-cell lymphoma (DLBCL), the male incidence is higher, and the prognosis is worse compared to females. The reasons are unclear; however, epidemiological and experimental data suggest that estrogens are involved. With this in mind, we analyzed gene expression data from a publicly available cohort (EGAD00001003600) of 746 DLBCL samples based on RNA sequencing. We found 1293 genes to be differentially expressed between males and females (adj. p-value < 0.05). Few autosomal genes and pathways showed common sex-regulated expression between germinal center B-cell (GCB) and activated B-cell lymphoma (ABC) DLBCL. Analysis of differentially expressed genes between pre- vs. postmenopausal females identified 208 GCB and 345 ABC genes, with only 5 being shared. When combining the differentially expressed genes between females vs. males and pre- vs. postmenopausal females, nine putative estrogen-regulated genes were identified in ABC DLBCL. Two of them, NR4A2 and MUC5B, showed induced and repressed expression, respectively. Interestingly, NR4A2 has been reported as a tumor suppressor in lymphoma. We show that ABC DLBCL females with a high NR4A2 expression showed better survival. Inversely, MUC5B expression causes a more mali

In follicular lymphoma (FL), progression of disease <= 24 months (POD24) has emerged as an important prognostic marker for overall survival (OS). We aimed to investigate survival more broadly by timing of progression and treatment in a national population-based setting. We identified 948 stage II-IV indolent FL patients in the Swedish Lymphoma Register diagnosed 2007-2014 who received first-line systemic therapy, followed through 2020. Hazard ratios (HRs) with 95% confidence intervals (CIs) were estimated by first POD at any time during follow-up using Cox regression. OS was predicted by POD using an illness-death model. During a median follow-up of 6.1 years (IQR: 3.5-8.4), 414 patients experienced POD (44%), of which 270 (65%) occurred <= 24 months. POD was represented by a transformation in 15% of cases. Compared to progression-free patients, POD increased all-cause mortality across treatments, but less so among patients treated with rituximab(R)-single (HR = 4.54, 95% CI: 2.76-7.47) than R-chemotherapy (HR = 8.17, 95% CI: 6.09-10.94). The effect of POD was similar following R-CHOP (HR = 8.97, 95% CI: 6.14-13.10) and BR (HR = 10.29, 95% CI: 5.60-18.91). The negative impact of POD on survival remained for progressions up to 5 years after R-chemotherapy, but was restricted to 2 years after R-single. After R-chemotherapy, the 5-year OS conditional on POD occurring at 12, 24, and 60 months was 34%, 46%, and 57% respectively, versus 78%, 82%, and 83% if progression-free. To conclude, POD before but also beyond 24 months is associated with worse survival, illustrating the need for individualized management for optimal care of FL patients.

Recent transcriptomic-based analysis of diffuse large B cell lymphoma (DLBCL) has highlighted the clinical relevance of LN fibroblast and tumor-infiltrating lymphocyte (TIL) signatures within the tumor microenvironment (TME). However, the immunomodulatory role of fibroblasts in lymphoma remains unclear. Here, by studying human and mouse DLBCL-LNs, we identified the presence of an aberrantly remodeled fibroblastic reticular cell (FRC) network expressing elevated fibroblast activated protein (FAP). RNA-Seq analyses revealed that exposure to DLBCL reprogrammed key immunoregulatory pathways in FRCs, including a switch from homeostatic to inflammatory chemokine expression and elevated antigen-presentation molecules. Functional assays showed that DLBCL-activated FRCs (DLBCL-FRCs) hindered optimal TIL and chimeric antigen receptor (CAR) T cell migration. Moreover, DLBCL-FRCs inhibited CD'+ TIL cytotoxicity in an antigen-specific manner. Notably, the interrogation of patient LNs with imaging mass cytometry identified distinct environments differing in their CD'+ TIL-FRC composition and spatial organization that associated with survival outcomes. We further demonstrated the potential to target inhibitory FRCs to rejuvenate interacting TILs. Cotreating organotypic cultures with FAP-targeted immunostimulatory drugs and a bispecific antibody (glofitamab) augmented antilymphoma TIL cytotoxicity. Our study reveals an immunosuppressive role of FRCs in DLBCL, with implications for immune evasion, disease pathogenesis, and optimizing immunotherapy for patients.

Comprehensive and scalable proteomic profiling of plasma samples can improve the screening and diagnosis of cancer patients. Here, the authors use the Olink Proximity Extension Assay technology to characterise the plasma proteomes of 1477 patients across twelve cancer types, and use machine learning to obtain a protein panel for cancer classification. A comprehensive characterization of blood proteome profiles in cancer patients can contribute to a better understanding of the disease etiology, resulting in earlier diagnosis, risk stratification and better monitoring of the different cancer subtypes. Here, we describe the use of next generation protein profiling to explore the proteome signature in blood across patients representing many of the major cancer types. Plasma profiles of 1463 proteins from more than 1400 cancer patients are measured in minute amounts of blood collected at the time of diagnosis and before treatment. An open access Disease Blood Atlas resource allows the exploration of the individual protein profiles in blood collected from the individual cancer patients. We also present studies in which classification models based on machine learning have been used for the identification of a set of proteins associated with each of the analyzed cancers. The implication for cancer precision medicine of next generation plasma profiling is discussed.

Diffuse large B cell lymphoma (DLBCL) is one of the most common types of aggressive lymphoid malignancies. Here, we explore the contribution of RNA editing to DLBCL pathogenesis. We observed that DNA mutations and RNA editing events are often mutually exclusive, suggesting that tumors can modulate pathway outcomes by altering sequences at either the genomic or the transcriptomic level. RNA editing targets transcripts within known disease-driving pathways such as apoptosis, p53 and NF-kappa B signaling, as well as the RIG-I-like pathway. In this context, we show that ADAR1-mediated editing within MAVS transcript positively correlates with MAVS protein expression levels, associating with increased interferon/NF-kappa B signaling and T cell exhaustion. Finally, using targeted RNA base editing tools to restore editing within MAVS 3 ' UTR in ADAR1-deficient cells, we demonstrate that editing is likely to be causal to an increase in downstream signaling in the absence of activation by canonical nucleic acid receptor sensing.

Comprehensive and scalable proteomic profiling of plasma samples can improve the screening and diagnosis of cancer patients. Here, the authors use the Olink Proximity Extension Assay technology to characterise the plasma proteomes of 1477 patients across twelve cancer types, and use machine learning to obtain a protein panel for cancer classification. A comprehensive characterization of blood proteome profiles in cancer patients can contribute to a better understanding of the disease etiology, resulting in earlier diagnosis, risk stratification and better monitoring of the different cancer subtypes. Here, we describe the use of next generation protein profiling to explore the proteome signature in blood across patients representing many of the major cancer types. Plasma profiles of 1463 proteins from more than 1400 cancer patients are measured in minute amounts of blood collected at the time of diagnosis and before treatment. An open access Disease Blood Atlas resource allows the exploration of the individual protein profiles in blood collected from the individual cancer patients. We also present studies in which classification models based on machine learning have been used for the identification of a set of proteins associated with each of the analyzed cancers. The implication for cancer precision medicine of next generation plasma profiling is discussed.

Recent transcriptomic-based analysis of diffuse large B cell lymphoma (DLBCL) has highlighted the clinical relevance of LN fibroblast and tumor-infiltrating lymphocyte (TIL) signatures within the tumor microenvironment (TME). However, the immunomodulatory role of fibroblasts in lymphoma remains unclear. Here, by studying human and mouse DLBCL-LNs, we identified the presence of an aberrantly remodeled fibroblastic reticular cell (FRC) network expressing elevated fibroblast activated protein (FAP). RNA-Seq analyses revealed that exposure to DLBCL reprogrammed key immunoregulatory pathways in FRCs, including a switch from homeostatic to inflammatory chemokine expression and elevated antigen-presentation molecules. Functional assays showed that DLBCL-activated FRCs (DLBCL-FRCs) hindered optimal TIL and chimeric antigen receptor (CAR) T cell migration. Moreover, DLBCL-FRCs inhibited CD'+ TIL cytotoxicity in an antigen-specific manner. Notably, the interrogation of patient LNs with imaging mass cytometry identified distinct environments differing in their CD'+ TIL-FRC composition and spatial organization that associated with survival outcomes. We further demonstrated the potential to target inhibitory FRCs to rejuvenate interacting TILs. Cotreating organotypic cultures with FAP-targeted immunostimulatory drugs and a bispecific antibody (glofitamab) augmented antilymphoma TIL cytotoxicity. Our study reveals an immunosuppressive role of FRCs in DLBCL, with implications for immune evasion, disease pathogenesis, and optimizing immunotherapy for patients.

Diffuse large B cell lymphoma (DLBCL) is one of the most common types of aggressive lymphoid malignancies. Here, we explore the contribution of RNA editing to DLBCL pathogenesis. We observed that DNA mutations and RNA editing events are often mutually exclusive, suggesting that tumors can modulate pathway outcomes by altering sequences at either the genomic or the transcriptomic level. RNA editing targets transcripts within known disease-driving pathways such as apoptosis, p53 and NF-kappa B signaling, as well as the RIG-I-like pathway. In this context, we show that ADAR1-mediated editing within MAVS transcript positively correlates with MAVS protein expression levels, associating with increased interferon/NF-kappa B signaling and T cell exhaustion. Finally, using targeted RNA base editing tools to restore editing within MAVS 3 ' UTR in ADAR1-deficient cells, we demonstrate that editing is likely to be causal to an increase in downstream signaling in the absence of activation by canonical nucleic acid receptor sensing.

Simple Summary Females show a favorable sex difference in incidence as well as in survival for many cancer types, so also in lymphoma. The reasons for this are unknown. We have therefore analyzed global gene expression in a large cohort of the most common lymphoma type, diffuse large B-cell lymphoma. We show that many genes are differentially expressed between males and females. Furthermore, the results demonstrate sex-dependent differences in gene expression between DLBCL subtypes. In addition, gene expression differs in pre- vs. postmenopausal women suggesting that estrogen regulation of genes is involved. Thus, estrogens may contribute to the sex and female age differences in incidence and prognosis observed. For most lymphomas, including diffuse large B-cell lymphoma (DLBCL), the male incidence is higher, and the prognosis is worse compared to females. The reasons are unclear; however, epidemiological and experimental data suggest that estrogens are involved. With this in mind, we analyzed gene expression data from a publicly available cohort (EGAD00001003600) of 746 DLBCL samples based on RNA sequencing. We found 1293 genes to be differentially expressed between males and females (adj. p-value < 0.05). Few autosomal genes and pathways showed common sex-regulated expression between germinal center B-cell (GCB) and activated B-cell lymphoma (ABC) DLBCL. Analysis of differentially expressed genes between pre- vs. postmenopausal females identified 208 GCB and 345 ABC genes, with only 5 being shared. When combining the differentially expressed genes between females vs. males and pre- vs. postmenopausal females, nine putative estrogen-regulated genes were identified in ABC DLBCL. Two of them, NR4A2 and MUC5B, showed induced and repressed expression, respectively. Interestingly, NR4A2 has been reported as a tumor suppressor in lymphoma. We show that ABC DLBCL females with a high NR4A2 expression showed better survival. Inversely, MUC5B expression causes a more mali

In follicular lymphoma (FL), progression of disease <= 24 months (POD24) has emerged as an important prognostic marker for overall survival (OS). We aimed to investigate survival more broadly by timing of progression and treatment in a national population-based setting. We identified 948 stage II-IV indolent FL patients in the Swedish Lymphoma Register diagnosed 2007-2014 who received first-line systemic therapy, followed through 2020. Hazard ratios (HRs) with 95% confidence intervals (CIs) were estimated by first POD at any time during follow-up using Cox regression. OS was predicted by POD using an illness-death model. During a median follow-up of 6.1 years (IQR: 3.5-8.4), 414 patients experienced POD (44%), of which 270 (65%) occurred <= 24 months. POD was represented by a transformation in 15% of cases. Compared to progression-free patients, POD increased all-cause mortality across treatments, but less so among patients treated with rituximab(R)-single (HR = 4.54, 95% CI: 2.76-7.47) than R-chemotherapy (HR = 8.17, 95% CI: 6.09-10.94). The effect of POD was similar following R-CHOP (HR = 8.97, 95% CI: 6.14-13.10) and BR (HR = 10.29, 95% CI: 5.60-18.91). The negative impact of POD on survival remained for progressions up to 5 years after R-chemotherapy, but was restricted to 2 years after R-single. After R-chemotherapy, the 5-year OS conditional on POD occurring at 12, 24, and 60 months was 34%, 46%, and 57% respectively, versus 78%, 82%, and 83% if progression-free. To conclude, POD before but also beyond 24 months is associated with worse survival, illustrating the need for individualized management for optimal care of FL patients.