ORIGINAL RESEARCH article

Front. Oncol., 03 September 2025

Sec. Head and Neck Cancer

Volume 15 - 2025 | https://doi.org/10.3389/fonc.2025.1667226

Prognosis of second primary oral squamous cell carcinoma after hematologic malignancy: a retrospective cohort analysis

    HY

    Huajiao Yu 1,2†

    BL

    Bo Li 1†

    YH

    Yu Huang 1

    XZ

    Xue Zhang 1

    HZ

    Hanchen Zhou 1

    ZF

    Zhien Feng 1*

    ZH

    Zhengxue Han 1*

  • 1. Department of Oral and Maxillofacial-Head and Neck Oncology, Beijing Stomatological Hospital, Capital Medical University, Beijing, China

  • 2. Department of Oral and Maxillofacial Surgery, Affiliated Hospital of Inner Mongolia Medical University, Hohhot, Inner Mongolia, China

Article metrics

View details

942

Views

266

Downloads

Abstract

Backgrounds:

Prognosis and optimal management strategies of second primary oral squamous cell carcinoma (OSCC) following a history of hematologic malignancies (HM) remain uncertain. We investigated whether HM history affects OSCC outcomes or necessitates treatment modifications.

Patients and methods:

This retrospective cohort study included 2486 OSCC patients: 14 with OSCC as a second primary malignancy post-HM (SPM group) and 2472 with primary OSCC (non-SPM group). Using propensity score matching (PSM), we created two cohorts: 1:17 (13 SPM vs 232 non-SPM) and 1:3 (13 SPM vs 38 non-SPM). Outcomes were disease-free survival (DFS), overall survival (OS), and disease-specific survival (DSS). Survival differences were analyzed using log-rank tests. Multivariate Cox regression identified prognostic predictors.

Results:

No significant survival differences existed between SPM and non-SPM groups in either cohort (1:17: DFS 53.8% vs 68.9%, p=0.102; OS 69.2% vs 81.3%, p=0.170; DSS 69.2% vs 82.2%, p=0.147. 1:3: DFS 53.8% vs 63.2%, p=0.302; OS 69.2% vs 76.3%, p=0.532; DSS 69.2% vs 78.9%, p=0.430). Cox regression identified independent predictors: DFS: Age (p=0.001), T stage (p<0.001), N stage (p<0.001); OS and DSS: Age (p<0.001), T stage (p<0.001), N stage (p<0.001), pathological grade (p<0.001), prior HM was not an independent predictor.

Conclusions:

A history of HM does not independently predict the prognosis of second primary OSCC nor necessitate modifications to standard OSCC treatment.

Introduction

Oral squamous cell carcinoma (OSCC) is one of the most prevalent head and neck malignancies, accounting for over 90% of oral cancers (1, 2). Despite advances in surgical and adjuvant therapies, its 5-year survival rate remains around 50% (3, 4). Tumor prognosis is influenced by a complex interplay of clinical, biological, and systemic factors (5–7). Underlying systemic diseases may profoundly impact cancer development, treatment efficacy, and outcomes (8–10).

Among systemic comorbidities, prior malignancies represent a distinct clinical entity (11, 12). In patients with dual primary tumors, prognosis may be affected by the biological characteristics of both malignancies, cumulative treatment-related toxicities, immune microenvironment remodeling (13), and molecular interactions. Patients with hematologic malignancies (HM), such as leukemia or lymphoma, face elevated risks of secondary solid tumors, including OSCC, primarily due to factors such as treatment-induced DNA damage (14) and immune microenvironment alterations (13). Notably, persistent immunosuppression (15) and chronic inflammation (16) in these individuals may promote a tumor-permissive microenvironment.

Although second primary malignancies (SPM) in cancer survivors, particularly those with prior HM, are increasingly studied, the independent prognostic impact of HM history on subsequent OSCC remains not well characterized. These patients often present compounded challenges from cumulative immunosuppression (15), impaired bone marrow function, and heightened susceptibility to therapy-related carcinogenesis (14).

This study aims to compare OSCC prognosis between patients with and without a history of hematologic malignancy, specifically examining whether well-controlled prior HM confers additional risk. We further seek to evaluate whether standard OSCC treatment protocols adequately meet the needs of this subgroup or require modification. Our findings are expected to inform clinical decision-making and guide treatment optimization for patients burdened by complex oncologic histories.

Patients and methods

Participants

This research was conducted in accordance with the World Medical Association’s Declaration of Helsinki (2002 revision). Ethical approval was obtained from the Institutional Review Board of the Beijing Stomatological Hospital, Capital Medical University (approval number: CMUSH-IRB-KJ-PJ-2022-38).

The study cohort comprised 2486 patients with OSCC who received treatment at the Department of Oral and Maxillofacial-Head and Neck Oncology, Beijing Stomatological Hospital, Capital Medical University from January 2000 to December 2021.

Eligibility criteria

The tumors were reclassified in accordance with the 8th edition of the UICC/AJCC classification system, utilizing the initial clinical descriptions as the basis for restaging. The criteria for patient selection were as follows: (1) histopathological confirmation of malignant tumor, (2) the site of tumor is the oral and maxillofacial region. The exclusion criteria are as follows: (1) distant metastasis, (2) no surgical treatment received, (3) the lesion site is located in the oropharynx, jawbone and glands, (4) pathologically confirmed as non-squamous cell carcinoma.

Treatments

All patients in this study received surgical treatment and adjuvant therapy according to different stages and the regimens recommended by the NCCN guidelines, repair and reconstruction was performed if necessary.

Follow-up

All the enrolled patients received regular follow-ups. The follow-up for OSCC was conducted by the specialist of our center, while the follow-up for HM was carried out by the hematology physicians. All the follow-up results were recorded in the patients’ medical records, and the frequency for each patient is once every 3–6 months.

Definitions

In this study, the SPM group was defined as patients whose first primary malignancy was a hematologic malignancy (HM) and whose second primary malignancy was OSCC. Patients presenting with OSCC as their first primary malignancy were classified as non-SPM. Disease-free survival (DFS), overall survival (OS) and disease-specific survival (DSS) were used as outcome variables to evaluate prognosis. The interval from the initial surgery to recurrence or death was used to calculate the DFS. OS was defined from the time of the initial surgery to death or the last follow-up. DSS was defined from the time of the initial surgery to the death cause from cancer or the last follow-up.

Data analyses

Descriptive statistics were compiled to present the data in terms of frequencies and percentages. Comparative analysis of baseline demographic characteristics was conducted using the chi-square test for categorical variables. The Kaplan-Meier survival analysis was utilized to assess DFS, OS and DSS, with the log-rank test employed to evaluate the significance of differences between groups. Potential predictors were examined through cox proportional hazards regression analysis. All statistical tests were two-sided, with a significance level set at p<0.05. The statistical analyses were performed using SPSS software (version 21.0 for Windows) and R (version 4.3.1 for Windows).

To minimize selection bias, propensity score matching (PSM) was employed to balance the different groups in terms of baseline covariates, PSM could reduce confounding factors and improve comparability among different group, SPSS was used to implement PSM. We set the caliper value to 0.1 and the matching ratio of SPM group and non-SPM group to 1:17 (the sample size calculation is completed through PASS). Due to the sample size, a high proportion of matching may affect the results. Therefore, a matching ratio of 1:3 is also used for double testing of the results.

Results

Patients

A total of 3262 patients with oral and maxillofacial malignant tumors who met the study time were included, through the inclusion and exclusion criteria for screening, a total of 2486 patients were finally included in this study, among which 14 cases (0.6%) were in the SPM group and 2472 cases (99.4%) were in the non-SPM group (Figure 1).

Figure 1

Flowchart showing patient selection for a study. Starting with 3,262 oral and maxillofacial tumors, 2,873 were squamous cell carcinoma. After exclusions, 2,571 were oral cavity malignant tumors. Enrolled patients totaled 2,486, divided into 14 in the SPM group and 2,472 in the non-SPM group. Other categories include non-squamous cell carcinoma, oropharynx, jawbone, and gland sites (302), and distant metastasis with no surgery (85).

Flowchart for screening enrolled patients. Out of the 3262 patients, 2486 met the inclusion criteria. Among them, 14 were in the SPM group and 2472 were in the non-SPM group.

Among the 2486 patients, 1428 were male (57.4%) and 1058 were female (42.6%). Mean age was 59.6 years, with a slight predominance of younger patients (1259, 50.6%) over older patients (1227, 49.4%). The tongue was the most common site in the overall situation, with a total of 1084 cases (43.6%), followed by the gums (684, 27.5%), buccal (418, 16.8%), floor of the mouth (237, 9.5%), and hard palate (63, 2.5%). The distribution of T stages is as follows: 21 cases (0.8%) in Tis stage, 563 cases (22.7%) in T1 stage, 854 cases (34.3%) in T2 stage, 313 cases (12.6%) in T3 stage, 663 cases (26.7%) in T4a stage, and 72 cases (2.9%) in T4b stage; Most patients were at the N0 stage (1656 cases, 66.6%) at the time of diagnosis, followed by the N2 stage (459 cases, 18.4%), the N1 stage (327 cases, 13.2%), and the N3 stage (44 cases, 1.8%). Among them, 1016 patients had a history of smoking (40.9%), and 1470 patients had no history of smoking (59.1%). 817 patients had a history of alcohol consumption, while 1669 patients had no history of alcohol consumption. The survival curve of the total queue is shown in Figure 2.

Figure 2

Kaplan-Meier survival curves showing survival probabilities over time in months for three subgroups: (A) Blue curve, (B) Red curve, and (C) Green curve. Each plot includes censored data points marked with crosses. Survival probability generally decreases over time in all graphs.

Survival curves of all enrolled patients: (A) DFS; (B) OS; (C) DSS.

Baseline characteristics and disease management in the SPM cohort

The SPM cohort (n=14) comprised 9 males and 5 females. Primary hematologic malignancies included leukemia (n=9) and lymphoma (n=5), the treatment of the first primary malignancy of patients in the SPM group includes bone marrow transplantation, immunosuppression, chemotherapy, radiotherapy, and surgical therapy, which are combined into different treatment regimens. Mean age at first primary malignancy diagnosis was 36.6 years and 50.1 years for SPM diagnosis. SPM sites included tongue (n=6), buccal (n=4), gum (n=3), and hard palate (n=1). Tumor staging revealed Tis (n=1), T1 (n=3), T2 (n=7), T3 (n=1), and T4a (n=2) disease and all patients underwent surgical treatment for OSCC, one patient received adjuvant radiotherapy. All patients had negative lymph nodes (N0 stage). Seven patients reported tobacco use history and four reported alcohol use history (Table 1).

Table 1

Number Gender FM Age (FM) Treatment (FM) Age (SM) Site (SM) T stage N stage Tobacco/Alcohol
Patient 1 Male Leukemia 35 BMT+IST+CT 50 Tongue T3 N0 Yes/No
Patient 2 Male Leukemia 40 BMT+CT 48 Tongue T2 N0 Yes/Yes
Patient 3 Male Leukemia 33 BMT+CT 41 Buccal T2 N0 No/No
Patient 4 Male Leukemia 34 BMT+CT 43 Buccal T2 N0 No/No
Patient 5 Female Leukemia 14 BMT+CT 16 Buccal T1 N0 No/No
Patient 6 Female Leukemia 18 BMT+CT 27 Tongue T2 N0 No/No
Patient 7 Male Leukemia 33 BMT+CT 47 Tongue T2 N0 Yes/Yes
Patient 8 Male Leukemia 38 BMT+IST+CT 50 Buccal Tis N0 Yes/Yes
Patient 9 Male Lymphoma 59 CT 69 Hard Palate T2 N0 Yes/No
Patient 10 Male Lymphoma 53 CT+RT 63 Gum T4a N0 Yes/Yes
Patient 11 Female Lymphoma 70 CT+RT 76 Tongue T1 N0 No/No
Patient 12 Male Lymphoma 28 ST+CT 39 Gum T4a N0 Yes/No
Patient 13 Female Lymphoma 8 ST+CT+RT 66 Tongue T1 N0 No/No
Patient 14 Female Leukemia 50 CT 66 Gum T2 N0 No/No

Basic information of patients in the SPM group.

FM, first malignance; SM, second malignance; BMT, bone marrow transplantation; IST, immunosuppressive therapy; CT, chemotherapy; RT, radiotherapy; ST, surgical treatment.

Baseline characteristics after propensity score matching

PSM was performed using 1:17 and 1:3 ratio to screen out comparable datasets. Ultimately, in 1:17 matching a total of 232 patients were included in the matching cohort, with 13 cases in the SPM group and 219 cases in the non-SPM group, the baseline data are shown in Table 2. In another group of pairs matched at a ratio of 1:3, a total of 51 patients were included, including 13 in the SPM group and 38 in the non-SPM group (Table 3).

Table 2

Variable Non-SPM group (n=219) SPM group (n=13) p-value SMD
Age 0.681 0.077
 ≤60 122 8
 >60 97 5
Gender 0.410 0.004
 Male 109 8
 Female 110 5
Site 0.778 0.123
 Tongue 94 6
 Gum 75 3
 Buccal 42 3
 Hard palate 8 1
T stage 0.959 0.022
 T1 51 3
 T2 103 7
 T3 21 1
 T4 44 2
Pathological grade 0.507 0.086
 Well 138 7
 moderately 81 6
Tobacco use 0.382 0.033
 Yes 75 6
 No 144 7
Alcohol use 0.813 0.063
 Yes 57 3
 No 162 10

Patient characteristics after propensity score matching by 1:17.

Table 3

Variable Non-SPM group (n=38) SPM group (n=13) p-value SMD
Age 0.577 0.155
 ≤60 20 8
 >60 18 5
Gender 0.818 0.103
 Male 22 8
 Female 16 5
Site 0.843 0.120
 Tongue 13 6
 Gum 11 3
 Buccal 12 3
 Hard palate 2 1
T stage 0.985 <0.100
 T1 9 3
 T2 20 7
 T3 2 1
 T4 7 2
Pathological grade 0.799 0.100
 Well 22 7
 moderately 16 6
Tobacco use 0.811 <0.100
 Yes 19 6
 No 19 7
Alcohol use 0.878 <0.100
 Yes 8 3
 No 30 10

Patient characteristics after propensity score matching by 1:3.

Comparable prognosis in SPM and non-SPM groups

Kaplan-Meier analysis revealed no significant prognostic differences between groups. In the 1:17 matched cohort, DFS (53.8% vs. 68.9%, p=0.102), OS (69.2% vs. 81.3%, p=0.170) and DSS (69.2% vs. 82.2%, p=0.147) did not show significant statistical differences in SPM group and non-SPM group (Figure 3). The similar results were obtained in 1:3 matching cohort, which indicated that DFS (53.8% vs. 63.2%, p=0.302), OS (69.2% vs. 76.3%, p=0.532) and DSS (69.2% vs. 78.9%, p=0.430), no significant statistical difference was observed between SPM group and non-SPM group (Figure 4). These results suggest that among patients with prior hematologic malignancies, OSCC as a second primary malignancy confers no significantly different prognosis compared to OSCC as a first primary malignancy.

Figure 3

Three panels, labeled A, B, and C, each display survival curves comparing non-SPM and SPM groups over 200 months. All panels include curves, p-values, risk numbers, and censoring events. Panel A shows p=0.102, B shows p=0.170, and C shows p=0.147, all indicating survival probabilities over time.

Kaplan-Meier survival analysis of the PSM cohort (1:17 matching ratio). No statistically significant differences were observed between SPM group and non-SPM group. (A) DFS: 53.8% vs. 68.9% (p=0.102); (B) OS: 69.2% vs. 81.3% (p=0.170); (C) DSS: 69.2% vs. 82.2% (p=0.147).

Figure 4

Three panels (A, B, C) of survival curves display survival probability over time in months for two strata: non-SPM (blue) and SPM (red). Each panel includes a p-value and corresponding graphs for the number at risk and number of censorings. Panel A shows a p-value of 0.302, B of 0.532, and C of 0.430, with varying survival probabilities and changes over time across panels.

Kaplan-Meier survival analysis of the PSM cohort (1:3 matching ratio). No statistically significant differences were observed between SPM group and non-SPM group. (A) DFS: 53.8% vs. 63.2% (p=0. 0.302); (B) OS: 69.2% vs. 76.3% (p=0.532); (C) DSS: 69.2% vs. 78.9% (p=0.430).

Independent predictors were screened through Cox regression analysis

Multivariable Cox proportional hazards regression was performed to identify independent prognostic factors across survival endpoints. The analysis established age as a consistent predictor for all outcomes, with significantly increased risk observed for DFS (p=0.001), OS (p<0.001), and DSS (p<0.001). Similarly, advanced T stage and N stage demonstrated strong independent associations with reduced survival across all three endpoints (p<0.001 for each). Notably, pathological grade emerged as a powerful independent determinant for both OS (p<0.001) and DSS (p<0.001), suggesting its differential impact on survival outcomes (Supplementary Table 1).

Discussion

The prognosis of OSCC is multifactorial, with systemic health status representing a key determinant. Among systemic comorbidities, a history of prior malignancy—particularly HM—constitutes a distinct clinical entity.

HM may influence the development and progression of SPMs. First, HM inherently induce systemic immune impairment, including T-cell dysfunction, diminished NK-cell activity, and compromised humoral immunity (17–20), this significantly weakens immune surveillance against solid tumors (21, 22). Second, HM treatments further impact SPM risk: conventional radiotherapy and chemotherapy regimens exacerbate immune injury, causing persistent lymphocyte subset imbalances. These therapies represent a double-edged sword—while targeting malignant cells, they simultaneously inflict DNA damage on healthy tissues in a dose-dependent manner (23–25). Additionally, the risk of SPM in HM patients after CART treatment should also be vigilant (26). Consequently, immune reconstitution failure may not only enhance tumor aggressiveness in second primary cancers but also diminish responsiveness to immunotherapy. Collectively, systemic immune dysregulation and chronic inflammation establish a tumor-promoting milieu.

HM survivors frequently exhibit persistent antigenic stimulation and inflammatory microenvironments that facilitate OSCC pathogenesis through multiple molecular pathways. The neutrophil-to-lymphocyte ratio, a validated systemic inflammation biomarker, demonstrates significant correlation with OSCC prognosis (27, 28). In HM survivors, this pro-inflammatory state often persists due to underlying disease and prior therapies.

Importantly, the prognosis of HM patients developing into SPM is still not completely clear, and the reasons may be multi-faceted. On the one hand, the causes of SPM in HM patients are very complex. It may be related to the impact of the HM disease itself on the overall condition, or it may be related to the complex treatment plan of HM. On the other hand, such cases are usually few in number and it is difficult to complete effective statistical analysis.

Our large-sample cohort study specifically examined OSCC outcomes in patients with prior HM. While concerns historically existed regarding treatment planning for this population—given potential HM-related comorbidities and uncertain prognosis—our exploratory analysis provides clinical guidance. Current findings indicate that a history of well-controlled HM does not constitute an independent high-risk prognostic factor for OSCC. Thus, patients developing OSCC as SPM after HM should be considered for conventional OSCC therapy.

Study limitations include the relatively small SPM subgroup size, which constrains statistical power. Nevertheless, large-scale cohort analysis remains the optimal feasible approach. Future work will expand recruitment to strengthen these findings.

Conclusions

Following conventional OSCC therapy, no statistically significant difference in prognosis was observed between patients with OSCC as a second primary malignancy after HM and those with primary OSCC, indicating that treatment modification appears unnecessary for these patients.

Statements

Data availability statement

The original contributions presented in the study are included in the article/Supplementary Material. Further inquiries can be directed to the corresponding authors.

Ethics statement

The studies involving humans were approved by Institutional Review Board of the Beijing Stomatological Hospital, Capital Medical University. The studies were conducted in accordance with the local legislation and institutional requirements. Written informed consent for participation was not required from the participants or the participants’ legal guardians/next of kin in accordance with the national legislation and institutional requirements.

Author contributions

HY: Formal analysis, Writing – original draft, Visualization, Validation. BL: Formal analysis, Writing – original draft, Validation, Investigation. YH: Writing – original draft, Data curation. XZ: Writing – original draft, Formal analysis. HZ: Writing – original draft, Data curation. ZF: Writing – review & editing, Conceptualization, Supervision, Funding acquisition. ZH: Conceptualization, Methodology, Supervision, Resources, Funding acquisition, Writing – review & editing.

Funding

The author(s) declare that financial support was received for the research and/or publication of this article. The work was supported by National Natural Science Foundation of China (82370925).

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Generative AI statement

The author(s) declare that no Generative AI was used in the creation of this manuscript.

Any alternative text (alt text) provided alongside figures in this article has been generated by Frontiers with the support of artificial intelligence and reasonable efforts have been made to ensure accuracy, including review by the authors wherever possible. If you identify any issues, please contact us.

Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Supplementary material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fonc.2025.1667226/full#supplementary-material

References

  • 1

    Singh P Rai A Verma AK Alsahli MA Rahmani AH Almatroodi SA et al . Survival-based biomarker module identification associated with oral squamous cell carcinoma (OSCC). Biol (Basel). (2021) 10:760. doi: 10.3390/biology10080760

  • 2

    Badwelan M Muaddi H Ahmed A Lee KT Tran SD . Oral squamous cell carcinoma and concomitant primary tumors, what do we know? A review of the literature. Curr Oncol. (2023) 30:3721–34. doi: 10.3390/curroncol30040283

  • 3

    Olmedo I Martínez D Carrasco-Rojas J Jara JA . Mitochondria in oral cancer stem cells: Unraveling the potential drug targets for new and old drugs. Life Sci. (2023) 331:122065. doi: 10.1016/j.lfs.2023.122065

  • 4

    Xue N Wang Y Wang Z Zeng X Wang J Zhang X . Trends in immunotherapy for oral squamous cell carcinoma. Cell Oncol (Dordr). (2025). doi: 10.1007/s13402-025-01068-3

  • 5

    Sasahira T Kirita T . Hallmarks of cancer-related newly prognostic factors of oral squamous cell carcinoma. Int J Mol Sci. (2018) 19:2413. doi: 10.3390/ijms19082413

  • 6

    Battista RA Pini GM Finco A Corso F Galli A Arrigoni G et al . From tumor macroenvironment to tumor microenvironment: the prognostic role of the immune system in oral and lung squamous cell carcinoma. Cancers (Basel). (2024) 16:2759. doi: 10.3390/cancers16152759

  • 7

    Yamagata K Sawadaishi R Takaoka S Fukuzawa S Uchida F Ishibashi-Kanno N et al . The inflammatory markers and locoregional pathological results both have an impact on the prognosis of oral squamous cell carcinoma in patients who have undergone neck dissection. J Stomatol Oral Maxillofac Surg. (2025) 126:102040. doi: 10.1016/j.jormas.2024.102040

  • 8

    Lee YC Jung SH Shivakumar M Cha S Park WY Won HH et al . Polygenic risk score-based phenome-wide association study of head and neck cancer across two large biobanks. BMC Med. (2024) 22:120. doi: 10.1186/s12916-024-03305-2

  • 9

    Vale N Pereira M Mendes RA . Systemic inflammatory disorders, immunosuppressive treatment and increase risk of head and neck cancers-A narrative review of potential physiopathological and biological mechanisms. Cells. (2023) 12:2192. doi: 10.3390/cells12172192

  • 10

    Lysaght J Conroy MJ . The multifactorial effect of obesity on the effectiveness and outcomes of cancer therapies. Nat Rev Endocrinol. (2024) 20:701–14. doi: 10.1038/s41574-024-01032-5

  • 11

    Hwang KT Kim MJ Chu AJ Park JH Kim J Lee JY et al . Metachronous sporadic sextuple primary Malignancies including bilateral breast cancers. J Breast Cancer. (2020) 23:438–46. doi: 10.4048/jbc.2020.23.e21

  • 12

    Ye X Liu X Yin N Song W Lu J Yang Y et al . Successful first-line treatment of simultaneous multiple primary Malignancies of lung adenocarcinoma and renal clear cell carcinoma: A case report. Front Immunol. (2022) 13:956519. doi: 10.3389/fimmu.2022.956519

  • 13

    Shirasawa M Yoshida T Matsumoto Y Shinno Y Okuma Y Goto Y et al . Impact of chemoradiotherapy on the immune-related tumour microenvironment and efficacy of anti-PD-(L)1 therapy for recurrences after chemoradiotherapy in patients with unresectable locally advanced non-small cell lung cancer. Eur J Cancer. (2020) 140:28–36. doi: 10.1016/j.ejca.2020.08.028

  • 14

    Junk SV Förster A Schmidt G Zimmermann M Fedders B Haermeyer B et al . Germline variants in patients developing second Malignant neoplasms after therapy for pediatric acute lymphoblastic leukemia-a case-control study. Leukemia. (2024) 38:887–92. doi: 10.1038/s41375-024-02173-2

  • 15

    Drexler HG Quentmeier H . The LL-100 cell lines panel: tool for molecular leukemia-lymphoma research. Int J Mol Sci. (2020) 21:5800. doi: 10.3390/ijms21165800

  • 16

    Rai AK Panda M Das AK Rahman T Das R Das K et al . Dysbiosis of salivary microbiome and cytokines influence oral squamous cell carcinoma through inflammation. Arch Microbiol. (2021) 203:137–52. doi: 10.1007/s00203-020-02011-w

  • 17

    Montironi C Muñoz-Pinedo C Eldering E . Hematopoietic versus solid cancers and T cell dysfunction: looking for similarities and distinctions. Cancers (Basel). (2021) 13:284. doi: 10.3390/cancers13020284

  • 18

    Lu J Luo Y Rao D Wang T Lei Z Chen X et al . Myeloid-derived suppressor cells in cancer: therapeutic targets to overcome tumor immune evasion. Exp Hematol Oncol. (2024) 13:39. doi: 10.1186/s40164-024-00505-7

  • 19

    Caro J Braunstein M Williams L Bruno B Kaminetzky D Siegel A et al . Inflammation and infection in plasma cell disorders: how pathogens shape the fate of patients. Leukemia. (2022) 36:613–24. doi: 10.1038/s41375-021-01506-9

  • 20

    Qiu Y Zhao W . Precise diagnosis and treatment for peripheral T-cell lymphomas: From pathogenic mechanisms to innovative approaches. Innovation Med. (2024) 2:100048. doi: 10.59717/j.xinn-med.2024.100048

  • 21

    Wang J Matosevic S . Functional and metabolic targeting of natural killer cells to solid tumors. Cell Oncol (Dordr). (2020) 43:577–600. doi: 10.1007/s13402-020-00523-7

  • 22

    Mani N Andrews D Obeng RC . Modulation of T cell function and survival by the tumor microenvironment. Front Cell Dev Biol. (2023) 11:1191774. doi: 10.3389/fcell.2023.1191774

  • 23

    Feng Y Qian K Guo K Shi Y Zhou J Wang Z . Effectiveness and risk of second primary Malignancies after radiotherapy in major salivary gland carcinomas: A retrospective study using SEER database. Head Neck. (2024) 46:1201–9. doi: 10.1002/hed.27664

  • 24

    van den Boogaard WMC Komninos DSJ Vermeij WP . Chemotherapy side-effects: not all DNA damage is equal. Cancers (Basel). (2022) 14:627. doi: 10.3390/cancers14030627

  • 25

    Bai B Ma Y Liu D Zhang Y Zhang W Shi R et al . DNA damage caused by chemotherapy has duality, and traditional Chinese medicine may be a better choice to reduce its toxicity. Front Pharmacol. (2024) 15:1483160. doi: 10.3389/fphar.2024.1483160

  • 26

    Umyarova E Pei C Pellegrino W Zhao Q Sharma N Benson D et al . Second primary Malignancies following CAR T-cell therapy in patients with hematologic Malignancies. J Hematol Oncol. (2025) 18:30. doi: 10.1186/s13045-025-01676-4

  • 27

    Mishra V Giri R Hota S Senapati U Sahu SK . Neutrophil-to-lymphocyte ratio as a prognostic factor in oral squamous cell carcinoma - A single-institutional experience from a developing country. J Oral Maxillofac Pathol. (2021) 25:322–6. doi: 10.4103/0973-029X.325235

  • 28

    Truong AA Lee RH Wu X Algazi AP Kang H El-Sayed IH et al . Neutrophil-to-lymphocyte ratio and pembrolizumab outcomes in oral cavity squamous cell carcinoma. Otolaryngol Head Neck Surg. (2025) 172:548–55. doi: 10.1002/ohn.1088

Summary

Keywords

oral squamous cell carcinoma, hematologic malignancy, second primary malignancy, prognosis, surgical treatment

Citation

Yu H, Li B, Huang Y, Zhang X, Zhou H, Feng Z and Han Z (2025) Prognosis of second primary oral squamous cell carcinoma after hematologic malignancy: a retrospective cohort analysis. Front. Oncol. 15:1667226. doi: 10.3389/fonc.2025.1667226

Received

16 July 2025

Accepted

18 August 2025

Published

03 September 2025

Volume

15 - 2025

Edited by

Cheng Wang, Sun Yat-sen University, China

Reviewed by

Wei Han, Nanjing University, China

Jiannan Liu, Shanghai Jiao Tong University, China

Updates

Copyright

*Correspondence: Zhengxue Han, ; Zhien Feng,

†These authors have contributed equally to this work

Disclaimer

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

Outline

Figures

Cite article

Copy to clipboard


Export citation file


Share article

Article metrics